Interactions between particulate organic matter and dissolved organic matter in a weak dynamic bay revealed by stable isotopes and optical properties

Few studies have incorporated the tools of stable isotopes and optical properties to study the biogeochemical process of organic matter (OM), including particulate organic matter (POM) and dissolved organic matter (DOM), which prevents our comprehension of the interactions between POM and DOM in the marine environment. In this study, the origin, distribution, and fate of POM and DOM in Tieshangang Bay, a weak dynamic bay were investigated by measuring δ¹³C and δ¹⁵N of POM, dissolved organic carbon (DOC), and absorption and fluorescence of DOM (CDOM and FDOM). In the upper bay, POM source was mainly originated from terrestrial discharge, whereas the high fluorescence index (FI) indicated that external aquatic organism activity dominated DOM sources. In contrast, in the outer bay, the slightly increased δ¹³C and enriched δ¹⁵N of POM and enhanced fluorescence intensities of protein-like DOM components indicated the considerable contributions of the in situ biological activities to OM. A net addition of DOC and optical components of DOM occurred in both the upper and outer bays. The decomposition of terrestrial POM was responsible for the addition of DOM due to the weak dynamics in the upper bay, whereas the enhanced primary production and the strong decomposition of freshly produced POM jointly contributed to the addition of DOM in the outer bay. Our study suggests that hydrodynamics regulate the biogeochemistry and interactions of POM and DOM in the weak dynamic bay.

1 Introduction

Estuaries and coastal bays are transitional areas from terrestrial to oceanic ecosystems with typically complicated environments (Lin et al., 2019; He et al., 2022a). An estimated 0.5 Pg C of organic carbon (OC) was transported from rivers to the oceans each year (Bianchi, 2011; Gao et al., 2021a), and more than 90% OC is buried in coastal area (Huang et al., 2020). Thus, the dynamics of organic matter (OM), including particulate organic matter (POM) and dissolved organic matter (DOM) in the estuaries and coastal bays, are important for the global matter cycle and climate change (Tremblay et al., 2015; Karlsson et al., 2016; Qu et al., 2022).

However, the behavior of OM in estuaries and coastal bays is complicated due to the OM is supplied from multiple sources, including terrestrial plant detritus, soils, in-situ aquatic production and exogenous offshore marine environments sources (Ke et al., 2020; Samantaray and Sanyal, 2022; Akcay et al., 2022). Moreover, due to the complex hydrological conditions in the estuaries and bays, the OM dynamics in estuaries and bays are subject to high spatial and temporal variability (Liu et al., 2020a; Chen et al., 2021). In addition, the heterotrophy in the coastal oceans may increase the release of carbon dioxide (CO₂) by the decomposition (Blair and Aller, 2012; Sarma et al., 2014; Gao et al., 2021b). Previous studies also suggested that ~35% of the POM is labile and easily degraded by the microorganisms (Hedges et al., 1997; Sarma et al., 2014; Ye et al., 2017). Therefore, a systematic understanding of the origin, distribution, and sink of OM in estuaries and bays is essential (Gao et al., 2021a; Samantaray and Sanyal, 2022; Dan et al., 2022).

Stable isotopic compositions (δ¹³C and δ¹⁵N) of POM and the geochemical indicators (i.e., C/N ratio of the POM) are considered as useful tools to discriminate the source and sink of POM in marine environments. (Chen et al., 2021; Dan et al., 2022; Xia et al., 2022). For instance, the δ¹³C compositions of POM from terrestrial sources (-30‰ to -23‰) are different from marine sources (-22‰ to -19‰) (Meyers, 1994; Meyers, 1997). Similarly, the δ¹⁵N compositions of terrestrial vascular plants (-5‰ to 18‰) are higher than that of the marine OM (3‰ to 12‰) (Wada & Hattori, 1990). Additionally, the C/N ratios of POM can be used to identify the marine sources (5-8) and terrestrial source (≥20) (Meyers, 1997). In addition, in recent years, spectroscopic techniques have been used to assess its distribution, source and fate at land–sea interfaces (Chen et al., 2022b; Qu et al., 2022; Sun et al., 2022). For example, the absorption coefficients of certain wavelengths (e.g., 254 nm, 325 nm) can be regarded as the levels of chromophoric dissolved organic matter (CDOM). In addition, the spectral slopes (e.g., S_275-295) and specific UV absorbance (e.g., SUVA₂₅₄) are considered as reliable qualitative indices for the DOM molecular size and its aromaticity (Weishaar et al., 2003; Wang et al., 2021b; Sun et al., 2022). A small portion of CDOM is defined as fluorescent DOM (FDOM). The FDOM spectrum can be used to describe DOM quantity (i.e., intensities of various fluorescent components) (Chen et al., 2022b; Sun et al., 2022) and quality (i.e., humification index (HIX), biological index (BIX) and fluorescence index (FI)) (Stedmon & Bro, 2008; Huguet et al., 2009; Li et al., 2022b). The variations of these spectroscopic indices in the land–sea interface were also obvious (Gao et al., 2019; Sun et al., 2022), which can be applied to identify the anthropogenic and natural sources (Liu et al., 2020b; Li et al., 2022b), biogeochemical behaviors (Li et al., 2022a) and export fluxes, and responses to climate changes for DOM in these dynamic systems (Qu et al., 2020). The source and distribution of POM or DOM have been studied in some areas around the world (Kaiser et al., 2013; Liu et al., 2020a; Chen et al., 2021). However, to date, few studies have incorporated stable isotopes and optical properties to systematically explore the sources, biogeochemical behaviors and interactions of OM in water environment (Qu et al., 2022).

The Beibu Gulf is located in the northern South China Sea (NSCS), and is a newly emerging industrial region in China. Multiple water masses influence the Beibu Gulf and carry stable external nutrient and other materials into the Beibu gulf to sustain marine production (Lao et al., 2022). Thus, the Beibu Gulf is generally characterized with high productivity and rich biodiversity, and is becoming an important mariculture base and fishing ground (Xu et al., 2020; Lin et al., 2021). However, environmental contamination in the gulf have gradually increased over the past decades because anthropogenic activities such as sewage treatment, coastal aquaculture, industrial runoff, and agriculture have intensively accelerated nutrient inputs to Beibu Gulf coastal ecosystems, especially in the rainy season (Xu et al., 2021; Zhu et al., 2022). Tieshangang Bay is a weak dynamic process bay in northeastern Beibu Gulf due to no large river input, and the tide is the main factor influencing water exchange in the bay (Jiang et al., 2017). Tieshangang Bay is a representative coastal bay of Guangxi Province. The rapid industrialization and urbanization have caused serious pollution around the coastal area in the bay (Lao et al., 2022). Compared with large catchments, the seasonal variation and anthropogenic activities have more great impacts on the coastal bays (such as Tieshangang Bay) (Zhang et al., 2019; Zhao et al., 2021). Therefore, Tieshangang Bay is an ideal area to explore OM dynamics under the influences of the increasing land-based input during the rainy seasons.

In this study, POC, PN, δ¹³C, and δ¹⁵N of POM, DOC, CDOM and FDOM, associated with hydrological and environmental parameters, such as temperature, salinity, apparent oxygen utilization (AOU), nutrients (${\text{NH}}_4^{+}$, ${\text{NO}}_2^{-}$, ${\text{NO}}_3^{-}$, ${\text{PO}}_4^{3-}$) and chlorophyll-a (Chl a) were analyzed in Tieshangang Bay. We attempted to comprehensively understand the sources, distributions and interactions of POM and DOM, to quantify the connections between the POM and DOM, and to discuss the biogeochemical process of OM in the Tieshangang Bay.

2 Materials and methods

2.1 Study region

The Beibu Gulf is in the NSCS (Figure 1), covering an area of ~12.8 × 10⁴ km². Tieshangang Bay (109°26′ - 109°45′E; 21°28′-21°45′ N) is one of the most industrial and harbor bay in the Beibu Gulf. Due to a combination of semi-enclosed topographic restrictions, lack of riverine input, weak local sea currents, and diurnal tides, Tieshangang Bay has a low water exchange rate (Jiang et al., 2017). Moreover, the average water residence time in the Tieshangang Bay is 64.0 days (Pei et al., 2019). Recently, human activities, including industry, agriculture and fishing, have a significant impact on the ecological environment of the bay (Chen et al., 2022a; Gan et al., 2013). Additionally, Tieshangang Bay is affected by monsoon. The rainfall is heavy (~86% of the total) from April to October (wet season), which is much higher than that from the November to March of following year (dry season) (Figure 1C).

FIGURE 1

Figure 1 (A) Study location. WM, winter monsoon; SM, summer monsoon. (B) sampling sites in Tieshangang Bay, and (C) mean monthly rainfall (mm) from 2012-2021 in Beihai city. (https://en.tutiempo.net/) .

2.2 Sampling collection

The cruise with 20 stations was conducted in Tieshangang Bay during the early rainy season (March 31 - April 1, 2021). At each station, surface samples (at 0.5-m depth) and bottom samples (when the depth >10 m) were collected. However, the study only shows the picture of the surface layer due to the number of bottom samples is rare. To meet the needs of our study, based on the characteristics of hydrological and environmental parameters, stable isotope and optical properties, the study area was classified into two regions: the upper bay (Stations T1-T8) and the outer bay (Stations T9-T20) (Figure 1) (Chen et al., 2022a). Seawater samples were collected on the deck. The seawater samples were filtered using acid-cleaned 0.45-μm acetate cellulose filters and then stored at -20°C for nutrient measurement. Approximately 500 ml seawater was passed through a glass fiber membrane (47-mm, GF/F, Whatman) and then cryopreservation (-20°C) for postcruise Chl a analysis in the laboratory. Preweighed and precombusted 47-mm diameter filters (GF/F, Whatman) were used to collect POM (POC and PN), and the POM samples were cryo-preserved (-20°C) before analysis. Water samples for DOM analysis, including DOC, CDOM and FDOM, were filtered immediately using precleaned 0.45-µm pore cellulose acetate filters, and the filtrates were stored in high-density polyethylene (HDPE) vials at -20°C and dark condition before further treatment.

2.3 Measurements of DO, nutrients, Chl a and DOC

In the laboratory, the iodometric method was used to measure DO. Nutrient sample for the analysis of ${\text{NO}}_3^{-}$, ${\text{NO}}_2^{-}$, and ${\text{PO}}_4^{3-}$, was measured by a San⁺⁺ continuous flow analyzer (Skalar, Netherlands). The seawater sample for ${\text{NH}}_4^{+}$ was measured using spectrophotometry. 90% acetone was added to extract the Chl a from the GF/F filter, and the fluorometric method were used to obtain the Chl a (Lorenzen, 1967). The DOC concentrations were analyzed by the vario TOC analyzer (Elementar, Germany) under high-temperature (680°C) catalytic oxidation mode. DOC concentrations were obtained by potassium hydrogen phthalate standards. The reproducibility of duplicate measurement for DOC analysis was 2%.

2.4 TSM, POC, PN and isotope analyses

The concentrations of total suspended matter (TSM) were measured from the weight of suspended sediment in filter by the volume of water. For POC and PN, the dried filters were placed in the bottle containing concentrated HCl vapor for decarbonation, and then washed using deionized water and dried at 50°C for two days (48 h). Then, the treated filters were introduced into an elemental analysis isotope ratio mass spectrometer (MAT 253 plus, EA-IRMS) for the analysis of POC and PN. The average standard deviation for δ¹³C and δ¹⁵N were all ±0.2‰, and for the contents of POC and PN were all ±0.1%.

2.5 CDOM analysis

Shimadzu UV-1780 dual beam spectrophotometer (Shimadzu, Japan) with 10-cm quartz cells was used to determine the CDOM absorbance spectra. Absorbance (A_λ) was obtained from wavelengths 240 and 800 nm at 0.5 nm intervals. The a_λ (CDOM Napierian absorption coefficient, m^-1) was calculated according to 2.303 times absorbance at wavelength λ (A_λ) divided by the light pathlength of the cell in meters (0.1 m). In this study, a₂₅₄ and a₃₂₅ and were used to quantify CDOM. (Wang et al., 2021a). Other popular wavelengths (e.g., 280 nm, 350 nm, 355 nm, 412 nm) of the CDOM absorption coefficients are presented in Table S1 to facilitate comparisons among different studies. The S_275-295 is a spectral slope between 275-295 nm, as an indicator of the relative molecular weight of DOM (Helms et al., 2008). The index for DOM aromaticity (SUVA₂₅₄, mg C L^-1) was calculated as decadal absorption coefficient (i.e., A(λ)/L) divided by the DOC concentration (Wang et al., 2021b).

2.6 FDOM analysis and PARAFAC modeling

The fluorescence spectrofluorometer (Hitachi F-7100, Japan) fitted with a 1-cm quartz cuvette was used to acquire the FDOM excitation-emission matrices (EEMs). The excitation (Ex) wavelengths spanned at 240-450 nm in 5 nm increments, and emission (Em) wavelengths spanned at 280-600 nm in 2 nm increments. The slit widths of emission and excitation were set to 5 nm and 10 nm, respectively. The fluorescence intensities are present in Raman units (R.U. nm^–1). HIX was used to identify the DOM humification degree (Zsolnay et al., 1999). BIX is used to indicate the new generated DOM in aquatic ecosystems (Huguet et al., 2009). FI is calculated to trace DOM sources (Cory and Mcknight, 2005). FI value > 1.9 denotes biological source of DOM, and the FI value<1.4 denotes the dominant terrestrial sources (Li et al., 2022b).

In this study, two humic-like components (C1: Ex/Em, ≤ 240, 290/390 nm, included peaks A and M; C2: Ex/Em, 260,360/440 nm, included peaks A and C) (Coble, 1996) and one protein-like component (C3: Ex/Em, 275/328 nm, peak T) (Coble, 1996) were identified in this study (Figure S1).

2.7 Two end-member mixing model

Salinity is one of the most important conservative parameters in seawater, a two end-member mixing model (the upper bay and outer bay end-member) was established in Tieshangang Bay to assess the biogeochemical behaviors of nutrients, DOC, CDOM and FDOM. For a discussion of nutrients, DOC, CDOM and FDOM sources and dynamics, in this study, because fluorescence intensities in T1 were no data, we selected the Station T2 water (salinity = 31.19) and the T18 water (salinity = 31.82) as the two end-members, respectively. The values of salinity, nutrients, DOC, CDOM and FDOM for the two end-members are shown in Table 1.

TABLE 1

Table 1 The chemical properties for the upper bay and outer bay end-members.

The salinity in each sample from Tieshangang Bay can be expected to follow Equations (1)-(2):

$\begin{array}{ll}{f}_{\text{u}}+f_{\text{o}}=1& (1)\end{array}$

$\begin{array}{ll}{f}_{\text{u}}Sa{l}_{\text{u}}+f_{\text{o}}Sa{l}_{\text{o}}=Sal& (2)\end{array}$

where f_u and f_o represent the fractions of the upper bay end-member and outer bay end-member in the sample, respectively. Based on the measured end-member values of nutrients, DOC, CDOM and FDOM (Table 1), the net-conservative changes (ΔN) in nutrients, DOC, CDOM and FDOM for a given sample can be calculated by subtracting its theoretical conservative mixing values as follows:

$\begin{array}{ll}\Delta N=N-f_{\text{u}}{N}_{\text{u}}-f_{\text{o}}{N}_{\text{o}}& (3)\end{array}$

where N denotes nutrients, DOC, CDOM or FDOM. Positive or negative ΔN values denote biogeochemical addition or removal processes during water mass mixing in Tieshangang Bay.

To further assess the robustness of this model and their derived net DOM values, we performed a perturbation test (Lønborg and Álvarez-Salgado, 2014). Here we assumed the salinity of two end-members fluctuates in the range of ±5%. For simplicity, a total of 50 perturbations test were conducted for the DOC. The valid tests showed the consistent results to the initial model (i.e., net addition of DOC with 0.14 ± 0.12 mg L^-1) and demonstrated the robustness of this model.

2.8 Bayesian mixing model

The Bayesian mixing model is used for quantification of potential POM sources in the Tieshanggang Bay in R software (MixSIAR v.3.1.10) (Chen et al., 2021), and the framework can be found in Supporting Information Text S1. The details of this model can be found in Lao et al. (2019). In addition, previous studies have shown that the Bayesian mixture models can be applied to quantify the origin of POM since different POM have different isotopic signatures (Kubo and Kanda, 2016; Chen et al., 2021).

2.9 Statistical analysis

The correlation analysis of different parameters and analysis of Student’s t-test of the difference between the parameters in the two groups were analyzed using SPSS 22.0.

3 Results

3.1 Physiochemical parameters

Figure 2 presents the basic physiochemical parameters for this cruise (Chen et al., 2022a). The temperature in the seawater ranged from 24.0 to 27.3°C (25.3 ± 0.68°C average). Salinity in the seawater ranged from 30.59 to 31.82 (with an average of 31.55 ± 0.27). The salinity increased seaward indicating that it is influenced by coastal freshwater discharge. AOU values were in the range of -0.97 and 1.25 mg L^-1(averaged at 0.42 ± 0.61 mg L^-1), showing a decreasing tendency seaward. The Chl a concentration ranged from 0.90-2.80 μg L^-1 (averaged at 1.75 ± 0.53 μg L^-1) and showed high values in the outer bay. Obviously, nutrients (${\text{NH}}_4^{+}$, ${\text{NO}}_2^{-}$, ${\text{NO}}_3^{-}$, ${\text{PO}}_4^{3-}$) were decreased seaward. The ${\text{NH}}_4^{+}$, ${\text{NO}}_2^{-}$, ${\text{NO}}_3^{-}$ and ${\text{PO}}_4^{3-}$ concentrations ranged from 0.60 to 2.31 μmol L^-1 (1.26 ± 0.58 μmol L^-1average), 0.05 to 1.28 μmol L^-1 (0.46 ± 0.31 μmol L^-1 average), 0.23 to 10.07 μmol L^-1 (3.27 ± 2.70 μmol L^-1average) and 0.02 to 0.92 μmol L^-1 (0.25 ± 0.25 μmol L^-1average), respectively. Notably, ${\text{NO}}_3^{-}$ is the dominant DIN in Tieshangang Bay.

FIGURE 2

Figure 2 Spatial variations of (A) temperature, (B) salinity, (C) AOU, (D) Chl a, and nutrients [(E) ${\text{NH}}_4^{+}$, (F) ${\text{NO}}_2^{-}$, (G) ${\text{NO}}_3^{-}$, (H) ${\text{PO}}_4^{3-}$] in Tieshangang Bay. Black dots donate sampling sites.

3.2 POC, PN, TSM, C/N ratios, δ¹³C, and δ¹⁵N

The concentrations of POC and PN ranged from 0.38-0.82 mg L^-1 (0.49 ± 0.11 mg L^-1average) and from 0.03 mg L^-1 to 0.09 mg L^-1 (0.05 ± 0.01 mg L^-1average), respectively. Generally, higher POC and PN concentrations were found in T8 and T19 in the outer bay (Figure 3). In addition, POC% and PN% in TSM varied between 1.49% and 4.92% (2.31 ± 0.72% average), 0.14% and 0.42% (0.23 ± 0.07% average), respectively.

FIGURE 3

Figure 3 Spatial variations of (A) POC, (B) PN, (C) POC%, (D) PN%, (E) TSM, (F) C/N, (G) δ¹³C (H) δ¹⁵N in Tieshangang Bay. Black dots are sampling sites.

The TSM concentration ranged from 16.60 to 37.60 mg L^-1 (averaged at 22.12 ± 4.95 mg L^-1), and the highest concentration was found in the upper bay (T8). The C/N values varied between 9.8-13.2 (11.90 ± 1.33 average) and presented a fluctuation across the bay. The δ¹³C values varied from -26.6‰ to -23.0‰ (averaged at -25.3 ± 0.9‰) and increased seaward. The δ¹⁵N values ranged from 1.5‰ to 8.1‰ (5.5 ± 2.0‰ average) and increased seaward (Figure 3).

3.3 Distributions of DOC, CDOM and FDOM

The distributions of DOC, CDOM and FDOM parameters are shown in Figures 4, 5. The concentrations of DOC ranged from 0.38 to 1.25 mg L^-1, averaged at 0.77 ± 0.23 mg L^-1. The highest DOC concentrations were observed at Station T9, while lower DOC concentrations were observed at Stations T11, T18 and T20. Interestingly, DOC concentrations were nearly homogeneous in the upper bay. The CDOM absorption coefficient at 254 nm (a₂₅₄) ranged from 1.73 to 5.64 m^-1 in the waters of Tieshangang Bay, averaged at 2.87 ± 0.78 m^-1 (Figure 4A). Generally, the a₂₅₄ value decreased seaward. The CDOM absorption coefficients at five longer wavelengths (a₂₈₀, a₃₂₅, a₃₅₀, a₃₅₅, a₄₁₂) show significant positive relation (p< 0.01, n = 26). Therefore, for simplicity, we report only the a₃₂₅ result. The a₃₂₅ value ranged from 0.41 to 1.50 m^-1, averaged at 0.72 ± 0.21 m^-1. a₃₂₅ were a significantly correlated with a₂₅₄ (R² = 0.96, p< 0.01, n = 26) and had a similar distribution pattern of a₂₅₄ in Tieshangang Bay (Figure 4C). The spectral slope S_275-295 (20.9-24.2 μm^-1) showed a contrasting spatial pattern with a₂₅₄ and a₃₂₅ (Figure 4D). A higher average value of S_275-295 was obtained in the outer bay than in the upper bay (t-test, p< 0.001). The SUVA₂₅₄ ranged from 1.16 to 2.66 m² g⁻¹ C, averaged at 1.70 ± 0.44, and the highest SUVA₂₅₄ occurred in T1 (Figure 4E).

FIGURE 4

Figure 4 Spatial variations of (A) DOC (mg L^-1), (B) a₂₅₄ (m^-1), (C) a₃₂₅ (m^-1), (D) S_275-295 (μm^-1), and (E) SUVA₂₅₄ (m² g^-1 C) in Tieshangang Bay. Black dots are sampling sites.

FIGURE 5

Figure 5 Spatial variations of (A) C1 (10^-2 RU), (B) C2 (10^-2 RU), (C) C3 (10^-2 RU), (D) HIX and (E) BIX, (F) FI in Tieshangang Bay. Black dots denote sampling sites.

The humic-like C1 and C2 fluorescence intensity ranged from 5.62 × 10^-2 to 13.80 × 10^-2 RU and 2.80 × 10^-2 to 9.00×10^-2 RU, respectively, and they were correlated significantly (R² = 0.97, p< 0.01, n = 25). Except for two unusually high values on the west side of the outer bay (T9 and T13), the fluorescence intensities of humic-like C1 and C2 substantially decreased seaward (Figures 5A, B). The intensity of protein-like C3 were in the range of 4.39 × 10^-2 to 7.28 ×10^-2 RU. The C3 intensity was low and nearly homogeneous in the upper bay (average 5.44 ± 0.73 ×10^-2 RU), whereas it varied much more in the outer bay, with a high value point on the west side (T13) and a low value point on the south side (T20) (Figure 5C). HIX varied from 1.38 to 2.96 and generally decreased seaward (Figure 5D). By contrast, BIX varied from 1.10 to 1.54 and showed the opposite distribution pattern to HIX (Figure 5E). The FI varied from 2.46 to 2.64 and showed a slight fluctuation in Tieshangang Bay (Figure 5F).

4 Discussion

4.1 Different sources of POM in the upper and outer bays

Bulk POM at the upper stations showed lower POC (0.45 ± 0.08 mg L^-1) and PN (0.05 ± 0.02 mg L^-1) contents than those at the outer stations (Figure 3 and Table 2). A strong correlation between POC concentration versus PN concentration in the upper bay (p< 0.01, n= 11) demonstrated similar sources of the two components (Figure S2). In addition, the C/N was up to ~12 in the upper bay, together with more depleted δ¹³C (-25.3‰) and δ¹⁵N (3.6‰) (Table 2 and Figure 6), suggesting that the POM (Table 2 and Figure 6E) primarily comes from terrestrial sources. The lower POC% and PN% of TSM also suggested that more terrestrial sources contribute to POM in the upper bay (Table 1). Therefore, this region is dominated by the terrestrial POM (Guo et al., 2015; Chen et al., 2020). Generally, terrestrial organic matter (i.e., soil OM, sewage, C3 and C4 plants), freshwater phytoplankton and marine organic matter are potential contributions to POM. The δ¹³C and δ¹⁵N values of abovementioned sources are summarized in Table S2. In this study, a Bayesian mixing model was applied to confirm that the terrestrial organic matter dominated (79%) in the upper bay (Figure 7A). Although the higher nutrient occurred in the upper bay, the Chl a (1.65) was lower and the Bayesian mixing model showed that the contribution of marine organic matter and freshwater phytoplankton was only 8% and 13% (Figure 7A). We realized there may exist some other uncertainties influencing the estimation of potential POM source, such as the decomposition process. The decomposition of POM can modify the isotopic compositions of POM. However, previous studies indicated that the decomposition of OM has a virtually negligible change on δ¹³C (~1‰) (Gearing et al., 1984; Chen et al., 2021). Thus, the isotopic compositions of POM can be used to identify source in the Tieshangang Bay due to the negligible isotopic modification by the POM decomposition. Moreover, although it is difficult to accurately calculate the potential POM source, we believe that the quantification in this study can at least reflect the potential POM source at a large extent.

FIGURE 6

Figure 6 Variations of (A) DOC (mg L^-1), (B) a₂₅₄ (m^-1), (C) a₃₂₅ (m^-1), (D) C1 (10^-2 RU), (E) C2 (10^-2 RU), and (F) C3 (10^-2 RU) along with salinity in the water of Tieshangang Bay. The red stars denote the low-salinity and high-salinity end-members used in this study.

FIGURE 7

Figure 7 POM source contributions in the upper bay (A) and outer bay (B) of Tieshangang Bay. Soils is terrestrial soil organic matter, MO is marine organic matter, and FP is freshwater phytoplankton; terrigenous organic matter including C3, C4, soil, sewage.

TABLE 2

Table 2 Summary of the mean values of temperature (T), salinity (S), nutrients (${\text{NO}}_3^{-}$, ${\text{NO}}_2^{-}$, ${\text{NH}}_4^{+}$, ${\text{PO}}_4^{3-}$), DO, Chl a, TSM, POC, PN, POC%, PN%, δ¹³C, δ¹⁵N, C/N, POC/Chl a, DOC, a₂₅₄, a₃₂₅, S_275-295, SUVA₂₅₄, C1, C2, C3, HIX, BIX and FI values in the upper and outer bay of Tieshangang Bay.

In contrast, higher POC and PN contents (POC: 0.52 ± 0.13 mg L^-1; PN: 0.05 ± 0.01 mg L^-1) and enhanced POC% and PN% of the TSM were found in the outer bay (Table 2). The significant positive relationships between POC versus Chl a (p< 0.01, n = 15) and PN versus Chl a (p< 0.01, n = 15) suggest that POM is mainly related to in situ phytoplankton primary production (Figure S3) (Krishna et al., 2018; Lu et al., 2022). Additionally, lighter ¹²C and ¹⁴N isotopes can be uptaked and removed preferentially during thermodynamic and physiological processes (Li et al., 2021; Lu et al., 2022). Therefore, the slightly increased δ¹³C (-25.2 ‰) and enriched δ¹⁵N (6.9‰) found in the outer bay also supported the above inference (Figures 3G, H). Previous studies show that the slow water exchange rate were caused by the semi-enclosed topography, weak local sea currents, and diurnal tides in Tieshangang Bay (Jiang et al., 2017). Therefore, the terrigenous input may decrease seaward (Chen et al., 2022a). Increased Chl a level (1.83 μg L^-1) in the outer bay were triggered by the reduced turbidity in Tieshangang Bay (Qiu et al., 2019; Chen et al., 2021). As shown in the Figure 7B, Bayesian mixing model showed that the contribution of freshwater phytoplankton (from 13% to 20%) and marine organic matter (from 8% to 12%) increased seaward, since the primary production of OM is mainly supported by the phytoplankton in the seawater.

4.2 POM decomposition dominates the net addition of DOM in the weak dynamic upper bay

High salinity (> 31) and FI (> 1.9) were found in the upper bay, indicating that aquatic organism activity (phytoplankton production or bacterial transformation) dominated DOM sources in the upper bay (Li et al., 2022b; Jiang et al., 2021) (Figures 2B, 5F). This is quite different from the POM in the upper bay, which is mainly derived from terrestrial input. Based on the theoretically conservative mixing lines, remarkable net additions of DOC, CDOM and FDOM into the upper bay were found (Figure 6). A two end-member mixing model revealed that the average net values (Δ) of DOM were 0.12 mg L^-1 (ΔDOC), 0.32 m^-1 (Δa₂₅₄), 0.05 m^-1 (Δa₃₂₅), 1.07 × 10^-2 RU (ΔC1), 1.05 × 10^-2 RU (ΔC2) and 0.35 × 10^-2 RU (ΔC3) in the upper bay. Synchronously, the nutrients were also nonconservative, with 0.72 μmol L^-1 and 0.06 μmol L^-1 additions for ${\text{NO}}_3^{-}$ and ${\text{NO}}_2^{-}$, respectively (Figure 8). Generally, DOM in marine environments might be produced by particle desorption, the release of phytoplankton production, OM decomposition, in addition to allochthonous input (Guo et al., 2014; Hu et al., 2022);. The CDOM contents in the surface layers were similar to those in the bottom layers (such as T3, T4 and T6, depths > 10 m); however, the TSM concentrations in the surface layers were much lower than those in the bottom layers at these stations (Table S1). The lack of correlations between DOM and TSM parameters demonstrated that the direct desorption and dissolution of particles had less impact on DOM in the upper bay (Li et al., 2019; Sun et al., 2022). Both the original DOM parameters (DOC, CDOM, FDOM) and their Δ values were not related to Chl a (p > 0.05), suggesting that in situ phytoplankton primary production was also not the major factor responsible for the net addition of DOM in the upper bay. The lower BIX (average of 1.12 ± 0.02) (t-test, p< 0.001) also supported the above inference. Abundant terrigenous OM in the marine environments would increase the turbidity of seawater; although higher nutrient was found in the upper bay, the increase in the turbidity of seawater would not be conducive to the growth of phytoplankton in this area. In fact, based on the average net values (Δ) and the original values, the net additions of C3 produced by phytoplankton contributed 7% to the original C3 pool of the upper bay. Therefore, high turbidity may limit the phytoplankton growth, and the primary production may have a weak influence on the addition of DOM.

FIGURE 8

Figure 8 Relationships between (A) salinity and offset- ${\text{NH}}_4^{+}$, (B) salinity and $\Delta {\text{NO}}_2^{-}$, (C) salinity and $\Delta {\text{NO}}_3^{-}$, and (D) salinity and $\Delta {\text{PO}}_4^3$^- in the water column (upper bay and outer bay) of Tieshangang Bay. $\Delta {\text{NH}}_4^{+}$, $\Delta {\text{NO}}_2^{-}$, $\Delta {\text{NO}}_3^{-}$, and $\Delta {\text{PO}}_4^{3-}$ are the differences between the observed and expected values, obtained from the end-member mixing model.

The dramatic addition of DOC occurred in the upper bay and showed a magnitude comparable to that of CDOM and FDOM. It is therefore believed that the decomposition of DOM would not occur in the upper bay. In summary, we inferred that the microbial-mediated decomposition of terrestrial POM might be the major process that resulted in the net additions of DOC, CDOM and FDOM in the upper bay. The high POC/Chl a (>200) indicated that the decomposition of POM occurred in the upper bay (Figure 9) (Cifuentes and Fogel, 1988; Bardhan et al., 2014; Guo et al., 2015; Gawade et al., 2018). Notably, the original a₃₂₅ was not related to DOC in the upper bay (p > 0.05), while Δa₃₂₅ was significantly correlated with ΔDOC. This relationship further supported the above inference that the net addition of DOC and CDOM in the upper bay was mainly subjected to the decomposition of POM. Previous studies have confirmed that humic-like fluorescence increases during microbial decomposition incubations and microbial decomposition is therefore the main sink of humic-like (Wang et al., 2021b). Obviously, the decomposition process contributed 11% and 15% to the original C1 and C2 pools in the upper bay, respectively, which was consistent with the higher HIX in the upper bay. The coastal diluted water discharges might have carried more domestic sewage or bacteria into the sea (Lao et al., 2019; Lu et al., 2021; Mattioli et al., 2016); this process can result in water deterioration and POM decomposition. Previous studies have demonstrated that bacterial activity is a crucial factor that influences the composition of DOM and relates the conversion of POM to DOM. (Kaiser and Benner, 2008). In the northern Beibu Gulf, He et al. (2019) showed that the heterotrophic bacteria abundance of (11.01 ± 6.31) × 10⁵ cell/mL, and He et al. (2022b) demonstrate that heterotrophic bacteria abundance of 12.61 × 10⁵ cell/mL in the seawater; moreover, these studies suggested that the heterotrophic bacteria are densely distributed in the coastal water, and gradually reduce in the offshore. (He et al., 2019; He et al., 2022b). These further confirmed strong bacterial decomposition of POM. The hydrodynamic conditions are very weak due to very small runoff flowing into Tieshanggang Bay. Therefore, the tide controls the water exchange and results in the long water residence time in the upper bay (Jiang et al., 2017). Such hydrological features offered a good opportunity for full microbial decomposition of POM and caused the accumulation of additional DOM in the upper bay but not exported to the outer bay over time.

FIGURE 9

Figure 9 δ¹³C and POC/Chl a ratios in the water column of Tieshangang Bay.

4.3 The enhanced primary production and decomposition of autochthonous POM jointly contribute to the net addition of DOM in the outer bay

The CDOM (a₂₅₄ and a₃₂₅) decreased seaward. In addition, the original CDOM coefficients (a₂₅₄ and a₃₂₅) were positively related with the Chl a concentrations (p< 0.05, n = 15), indicating that DOM and POM may share the same source (i.e., phytoplankton production). Similar to DOM in the upper bay, the nonconservative behaviors of DOM in the outer bay were also profound. The average net values (Δ) of DOM were 0.23 mg L^-1 (ΔDOC), 0.64 m^-1 (Δa₂₅₄), 0.13 m^-1 (Δa₃₂₅), 2.38 × 10^-2 RU (ΔC1), 1.39 × 10^-2 RU (ΔC2) and 1.06 × 10^-2 RU (ΔC3) in the outer bay.

For the decomposition of POM, the POC/Chl a ratio raised from 279.08 in the upper bay to 308.93 in the outer bay, suggesting that POM decomposition was more intense than in the upper bay. The higher Chl a value, POC% and PN% of the TSM, slightly increased δ¹³C (-25.2 ‰) and enriched δ¹⁵N (6.9 ‰) confirmed that the increase of in situ phytoplankton production contributes greatly to POM in the outer bay. Previous studies suggested that the newly produced POM preferentially decomposed in the water column (Cifuentes and Fogel, 1988; Guo et al., 2015). Therefore, the abundance of fresh POM (i.e., fresh Chl a) is conducive to the heterotrophic process of bacteria in the outer bay. Additionally, the long water residence time provides good conditions for bacterial activity in the outer bay (Jiang et al., 2017; Chen et al., 2022a). As shown in Figure 10, the FDOM exhibited more positive Δ values in the outer bay, that is, the net values (Δ) of C1 were 2.2 times higher and the net values (Δ) of C2 were 1.3 times higher than those in the upper bay. Additionally, the decomposition process contributed 27% to the original C1 pool and 28% to the original C2 pool of the outer bay. These results also suggested that the more intense decomposition of POM occurred due to the freshly produced POM in the outer bay.

FIGURE 10

Figure 10 Net (A) DOC values (ΔDOC), (B) a₂₅₄ values (Δa₂₅₄), (C) a₃₂₅ values (Δa₃₂₅), (D) C 1 values (ΔC1), (E) C2 values (ΔC2), and (F) C3 values (ΔC3) in the water of Tieshangang Bay.

The positive net values (Δ) of C3 were 3.0 times higher than those in the upper bay, and this phenomenon may be related to phytoplankton-derived DOM. Phytoplankton production was considered to be one of the most important biogeochemical driver of DOM fluctuation in seawater. Therefore, the generation and accumulation of labile DOM (protein-like C3) were found in this highly productive region, consistent with the higher S_275-295 and lower SUVA₂₅₄ in the outer bay. Additionally, the positive net values (Δ) of C3 produced by phytoplankton contributed 19% to the original C3 pool of the outer bay, also confirming the increased contribution of primary production. Although decomposition of POM still occurred in the outer bay, unlike what was found in the upper bay, the nutrient decreased, and more nutrients showed a negative net (Δ) value in the outer bay (Figure 8), indicating that phytoplankton uptake affects nutrient levels in the outer bay. Phytoplankton growth in the outer bay is triggered by nutrient input from the decomposition of POM and reduced turbidity in the water column. Therefore, Chl a was the one of the most significant biogeochemical drivers of protein-like C3 fluctuation in the outer bay (Letourneau and Medeiros, 2019; Bowen et al., 2019; Chiranjeevulu et al., 2014; Loginova et al., 2016). Despite the decomposition of POM and the concomitant production of humic-like FDOM in the outer bay, however, the decrease in HIX indices ranged from 1.38 to 2.41, with an average of 1.94 ± 0.30, and the increase in BIX values varied from 1.13 to 1.54, with an average of 1.29 ± 0.11, all suggesting that they were connected with increasing autochthonous biological activity. Therefore, our data suggested that elevated primary production would have an important impact on the DOM pool in the outer bay.

Generally, protein-like are representative of the dynamics of the labile DOM pool, while humic-like materials can be produced as a byproduct of microbial DOM decomposition (Wang et al., 2021a; Wang et al., 2021b). In this study, the increase in protein-like C3 occurred in the outer bay, and the components were labile and linked to primary production in the water. This phenomenon suggested that the decomposition of POM was more intense than the decomposition of protein-like C3, as evidenced by the increased BIX values in the outer bay. Therefore, comparing with the upper bay, the addition of DOM was mainly caused by the decomposition of freshly produced POM (i.e., fresh Chl a) and planktonic production in the outer bay.

4.4 Implications for organic carbon circulation in the weak hydrodynamic bay

The sources and biogeochemistry of POM or DOM have been reported separately (Tremblay et al., 2015; Karlsson et al., 2016; Ke et al., 2020; Chen et al., 2021). However, few studies combined the indices of POM and DOM to systematically explore the sources and biogeochemical behaviors of OM (Qu et al., 2022);. The summary of the OM cycle in the Tieshangang Bay is presented in Figure 11. Overall, the weak hydrodynamics promoted a strong decomposition process that controlled the biogeochemistry of POM and DOM across the Tieshangng Bay, southern China, which provide a new insight of the carbon and nitrogen cycle in a coastal bay. In many coastal areas of the world, the circumstance, i.e., heterotrophy over autotrophy, not only causes water hypoxia and therefore deteriorates the marine ecosystem but also emits CO₂ through OM decomposition (Gawade et al., 2018) and generates positive feedback on global climate change (Laruelle et al., 2010; Wang et al., 2021a; Wang et al., 2021b; Hu et al., 2022). Moreover, the degradation processes of POM and DOM can be further explored with field culture experiments in in the future. Currently, global warming has caught people’s attention; thus, it is essential necessary to understand C and N cycling and step toward effective coastal management.

FIGURE 11

Figure 11 A brief diagram of the OM cycle in Tieshangang Bay.

5 Conclusion

By analyzing the δ¹³C and δ¹⁵N of POM, absorption and fluorescence of DOM, together with conventional geochemical indicators, the origin, distribution, and fate of POM and DOM was studies in Tieshangang Bay, a weak dynamic bay in the early rainy season. In the upper bay, POM source was mainly originated from terrestrial input, however, external aquatic organism activity dominated DOM sources. In contrast, considerable contributions of the in situ biological activities to OM in the outer bay. DOM did not show conservative mixing behavior in Tieshangang Bay, with net additions of DOC and optical components of DOM in both the upper and outer bays. The decomposition of terrestrial POM was the primary factor responsible for the additions of DOM in the upper bay, whereas the enhanced primary production and the strong decomposition of freshly produced POM jointly contributed to the net addition of DOM in the outer bay. Overall, the weak hydrodynamics promoted a strong decomposition process that controlled the biogeochemistry of POM and DOM across the Tieshangng Bay, southern China.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.

Author contributions

FC: Conceptualization, Funding acquisition. XL and QL: Writing-Original draft, Data Curation, Visualization, Software. XL and CW: Formal analysis. XL, QL, GJ, and CC: Investigation. CC: Methodology. FC: Project administration, Resources. FC: Supervision, Validation. FC, CW, QL, GJ, XZ, and XL: Writing-Review and Editing. All authors contributed to the article and approved the submitted version.

Funding

This study was supported by the National Natural Science Foundation of China (U1901213, 92158201), Guangdong Natural Science Foundation of China (2019B1515120066), Inovation and Entrepreneurship Project of Shantou (2021112176541391) and Guangxi Natural Science Foundation of China (2020GXNSFBA297065).

Acknowledgments

We would like to thank Marine Environmental Monitoring Centre of Beihai, State Oceanic Administration, for their assistance with collecting water samples.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2023.1144818/full#supplementary-material

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