Effects of plant invasion and land use change on soil labile organic carbon in southern China’s coastal wetlands

Highlights

	● EOC dominated the labile organic carbon pool in coastal wetland soil.
	● Invasion of mudflats by Spartina alterniflora increased soil EOC and DOC.
	● EOC and DOC decreased when Spartina marshes were converted into aquaculture ponds.
	● SOC mineralization rate increased most strongly with increasing DOC.
	● Latitudinal gradients in EOC and MBC suggest a temperature-dependent effect.

Abstract

Labile organic carbon (LOC) plays a pivotal role in soil biogeochemistry and ecological functions. China’s coastal wetlands have been profoundly impacted due to plant invasion and land use change, but the effects on soil LOC quantity and composition are unclear. This study analyzed the soil LOC components—namely, dissolved organic carbon (DOC), easily oxidizable carbon (EOC), and microbial biomass carbon (MBC)—across twenty-one coastal wetlands in southeastern China. These wetlands underwent a uniform land cover transition from native mudflats (MFs) to Spartina alterniflora marshes (SAs), and eventually to aquaculture ponds (APs). The results indicated that EOC was the dominant component of soil organic carbon (SOC) (57.5%–61.6%), followed by MBC (3.5%–4.5%) and DOC (<0.5%). The transition from MFs to SAs led to a rise in mean EOC and DOC by 18.6% and 41.4%, respectively. Subsequent conversion of SAs to APs resulted in a reduction in mean EOC and DOC by 5.9% and 20.3%, respectively. MBC did not differ significantly among habitat types. Total nitrogen availability was the main driver of changes in LOC across both land cover change scenarios. The mineralization rate of SOC were more strongly correlated with DOC than EOC and MBC. Microbial turnover of EOC was temperature dependent across the geographical range. These finds highlighted that plant invasion and land use change affected LOC fractions and subsequent SOC stability and carbon emissions in coastal wetlands.

Graphical abstract

Keywords

labile organic carbon (LOC) / dissolved organic carbon (DOC) / microbial biomass carbon (MBC) / carbon stock / plant invasion / aquaculture reclamation

1 Introduction

Soil is the most extensive reservoir of terrestrial organic carbon pool (Batjes, 2014; Li et al., 2024) with approximately 1500 Pg C (Lal, 2008; Scharlemann et al., 2014). Even a small change in the soil organic carbon (SOC) stock can substantially impact atmospheric levels of CO₂ and CH₄, thereby influencing the global carbon budget (Le Mer and Roger, 2001; Leifeld et al., 2019; Zhong et al., 2019). By influencing soil structure and nutrient availability (Haubensak et al., 2002; Hati et al., 2007; Zhang et al., 2018), the dynamics of SOC are also of vital importance to ecosystem functions (Wiesmeier et al., 2019; Hoffland et al., 2020).

The SOC pool contains both labile organic carbon (LOC) and recalcitrant organic carbon of different biochemical stabilities (Rovira and Vallejo, 2002; Cheng et al., 2007; Wang et al., 2012; Shao et al., 2022). LOC is linked to the source-sink dynamics of greenhouse gases (GHGs) such as CO₂ and CH₄ (Padhy et al., 2020; Yang et al., 2022). Hence, knowledge on the concentrations, types, and responses of LOC to environmental change is imperative for evaluating SOC stability and its climate feedback. The LOC pool consists of different components, including dissolved organic carbon (DOC), easily oxidizable carbon (EOC), and microbial biomass carbon (MBC) (Haubensak et al., 2002; Xiao et al., 2015). DOC by nature is soluble and more mobile through the soil and more accessible to microbes (Neff and Asner, 2001); the soil DOC stock is highly influenced by hydrological processes, and leaching of DOC is a main loss term in the soil carbon budget (Kindler et al., 2011). EOC by definition is the highly reactive portion of LOC that is operationally defined as the fraction quantified by the permanganate oxidation method (Culman et al., 2012), and its reactive nature makes it sensitive to land management practices and disturbances (Culman et al., 2012; Lucas and Weil, 2021). Because many vital ecological functions of soil are largely dependent on its microbial communities (Banerjee and van der Heijden, 2023), MBC provides a useful indicator of soil health (Fierer et al., 2021), and significant changes to MBC may signal a large variation in ecosystem state.

It is well established that SOC in terrestrial systems is strongly influenced by land use change (e.g., converting forests to farms) (Zhang et al., 2006; Sheng et al., 2015; Lu et al., 2023), land management practices (e.g., tillage, irrigation, fertilization, and crop rotation) (Yang et al., 2012; Bongiorno et al., 2019; Ramesh et al., 2019), vegetation coverage and vegetation type (Wang et al., 2011, 2021). Additionally, studies on terrestrial systems have shown a latitudinal increase in SOC coupled with a decrease in microbial turnover of SOC, demonstrating the effect of decreasing temperature and nutrient along the latitudes (Garten, 2011; Wang et al., 2012).

Despite research on the impact of plant invasion and land reclamation on SOC content in coastal wetlands (e.g., Soper et al., 2019; Tan et al., 2023; Wang et al., 2023), there is a notable scarcity of data on the different fractions of LOC. This knowledge gap limits our comprehension of changes in the properties and stability of SOC. Although coastal wetlands occupy a small proportion of global ocean's area, they accumulate 44.6–53.7 Tg C yr⁻¹ worldwide (Chmura et al., 2003; Wang et al., 2021) and are responsible for ~50% of the C burial in marine sediments (Mcleod et al., 2011; Duarte et al., 2013; Fu et al., 2021; Macreadie et al., 2021). High primary productivity, rapid sedimentation, and low oxygen levels allow coastal wetlands to sequester C for millennia (Atwood et al., 2017; Xu et al., 2022). However, numerous coastal wetlands globally are facing threats from invasion by alien species (Zhang et al., 2012; Lázaro-Lobo and Ervin, 2021; Ding et al., 2023; Wang and Lin, 2023), anthropogenic disturbances (e.g., land reclamation) and climate change (Newton et al., 2020; Fluet-Chouinard et al., 2023), which can alter soil LOC and biogeochemical processes.

Over the past decades, extensive areas of wetlands along China’s southeast coast have undergone a sequence of land cover change, first invasion of mudflats by Spartina alterniflora (Chung, 2006; Sun et al., 2015; Mao et al., 2019), followed by clearing of the Spartina marshes to create earthen aquaculture ponds (Ren et al., 2019; Duan et al., 2020; Wang et al., 2022b). These changes offer a unique opportunity to examine the sequential impacts of land cover change on wetland biogeochemistry across a large latitudinal range. Recently, we have begun to investigate the effect of this land cover change on various parameters, including soil C pools (Hong et al., 2023), mineral-bound OC (Yang et al., 2024) and SOC mineralization (Yang et al., 2022). As a companion study, here we analyzed the DOC, EOC, and MBC contents in the three different habitat types: native mudflats, S. alterniflora marshes, and aquaculture ponds, along the southeast coast of China. The primary aims of this study are to explore the change patterns of LOC components and the major driving factors across various land cover change scenarios and evaluate the importance of different LOC components in the mineralization of SOC within these affected coastal wetlands. Based on relevant findings in terrestrial systems, we hypothesized that the different soil LOC components would increase with vegetation coverage when mudflats were invaded by S. alterniflora, but subsequent conversion of S. alterniflora marshes to earthen aquaculture ponds would decrease soil LOC. Furthermore, we hypothesized that EOC and MBC would show opposite latitudinal trends indicating a latitudinal decline in microbial turnover of soil LOC.

2 Materials and methods

2.1 Study areas

The study covered twenty-one coastal wetlands across five regions of China including Guangxi Zhuang Autonomous Region, Guangdong Province, Fujian Province, Zhejiang Province and Shanghai City (Fig.1), spanning nearly 2500 km. These regions experience a tropical-to-subtropical monsoon climate, with an annual air temperature range of 11.0–23.0 ^oC and rainfall 1000–2200 mm each year (Yang et al., 2022). The total area of coastal wetlands in the regions was approximately 2.58 × 10⁴ km² (Sun et al., 2015). Initially, these wetlands were affected by S. alterniflora invasion of mudflats (Mao et al., 2019), followed by the transformation of S. alterniflora marshes into earthen aquaculture ponds, mainly for culturing Whiteleg shrimp (Ren et al., 2019). At the time of this study, S. alterniflora marshes and aquaculture ponds along these coastal zones covered approximately 3.34 × 10² km² (Liu et al., 2018) and 5.31 × 10³ km² (Duan et al., 2020), respectively.

Fig.1 Locations of the 21 coastal wetlands in southern China. These wetlands have undergone the same sequence of land cover change from native mudflats to S. alterniflora marshes then to earthen aquaculture ponds.

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2.2 Sample collection and analysis

During December 2019 and January 2020, soil samples were collected from the three habitats at each of the 21 coastal wetlands. In each of the mud flats (MFs) and S. alterniflora marshes (SAs), three random plots were chosen for sampling. For the aquaculture ponds (APs), sampling was carried out at three locations: one near the pond’s edge, another at the center, and one halfway between these two points. From each sampling site, three soil samples were extracted from the top 20 cm using a steel corer (length 1.5 m, diameter 0.05 m) and then mixed into a composite sample in a sterile plastic bag. This process resulted in a total of 189 soil samples (21 coastal wetlands × 3 habitat types × 3 replicate plots). All samples were transported in a cooler back to the laboratory for further analyses.

A subsample of the soil was used for measuring physicochemical properties including pH, salinity, soil water content (SWC), total nitrogen (TN), ammonia-nitrogen (${\text{NH}}_{\text{4}}^{+}$-N), particle size distribution, chloride (${\text{Cl}}^{-}$) and sulfate (${\text{SO}}_{\text{4}}^{\text{2}-}$). Detailed analytical methods and results are available in our associated publications (Yang et al., 2022, 2023; Hong et al., 2023). This study concentrated on examining soil LOC components and their relationships with various soil and environmental parameters.

2.3 Analysis of soil labile organic carbon components

EOC was analyzed using the KMnO₄ oxidation method adapted from Blair et al. (1995). Briefly, 0.2 g of air-dried soil, sieved to less than 2 mm, was added to 5 mL of 333 mM KMnO₄ solution in a 10-mL centrifuge tube. The mixture was then shaken at 250 r min^‒1 for 30 min on a rotary shaker, followed by 5 min centrifugation at 4000 r min^‒1. Afterward, 0.2 mL of the supernatant was diluted with deionized water to 50 mL (Cheng et al., 2024), and the diluted solution was measured for absorbance at 565 nm wavelength on a spectrophotometer (Shimadzu UV-2450, Japan) (Blair et al., 1995; Fan et al., 2024).

Determination of DOC followed the method outlined by Fang et al. (2020) and Zhang et al. (2007). Briefly, 2 g of fresh soil sample was added to 10 mL of deionized water in a 15-mL centrifuge tube. The mixture was shaken on an oscillator (IS-RDD3, China) at 250 r min^‒1 for 30 min, and subsequently centrifuged at 4000 r min^‒1 for 20 min. The resulting supernatant was passed through a 0.45-μm carbon-free membrane filter into a vial (Ghani et al., 2003; Xiao et al., 2015). The filtered supernatant was subsequently analyzed for DOC concentration using a Total Organic Carbon Analyzer (Schimadzu TOC-_VCPH, Kyoto, Japan).

To measure soil MBC, we employed a fumigation–extraction technique adapted from Vance et al. (1987) and Wang et al. (2022a). Briefly, approximately 10 g of fresh soil sample was fumigated with ethanol-free CHCl₃ for 24 h. Afterward, both the fumigated and unfumigated soil samples were extracted using a 0.5 M K₂SO₄ solution and agitated at 250 r min^‒1 for 30 min on a rotary shaker. The mixture was then centrifuged at 4000 rpm for 20 min. The supernatant was filtered through a 0.45-μm carbon-free membrane into a vial and the filtered supernatant was analyzed for total DOC. The MBC (mg C kg^‒1) in the soil was calculated as (Wang et al., 2012):

$\mathrm{M}\mathrm{B}\mathrm{C}=\frac{\mathrm{F}\mathrm{u}\mathrm{m}\mathrm{i}\mathrm{g}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{C}-\mathrm{U}\mathrm{n}\mathrm{f}\mathrm{u}\mathrm{m}\mathrm{i}\mathrm{g}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{C}}{{\mathit{K}}_{\mathrm{E}\mathrm{C}}}$

where Fumigated C (mg C kg^‒1) and Unfumigated C (mg C kg^‒1) were the extractable DOC in the respective samples. K_EC was the C fraction recovery from microbial biomass, which was taken to be 0.38 in this study (Vance et al., 1987; Li et al., 2010).

2.4 Statistical analysis

All data were tested for normality and homogeneity of variance. Statistical differences between soil LOC components (i.e., EOC, DOC and MBC) were assessed by one-way ANOVA in SPSS version 25.0 (IBM, Armonk, NY, USA). The influence of latitudinal gradients on soil LOC components was analyzed through linear regressions. The impact of various soil physicochemical properties on soil LOC components was examined using redundancy analysis (RDA) in CANOCO version 5.0 (Microcomputer Power, Ithaca, USA). The different LOC components as percentages of the total SOC were calculated based on SOC values from Hong et al. (2023). To quantify the influence of different land cover change scenarios on soil labile organic carbon fractions, weighted response ratios (RR₊₊) were calculated according to Hedges et al. (1999) and Tan et al. (2020). Furthermore, simple linear regressions were used to explore the relationships between SOC mineralization rate (R_min) and LOC components, utilizing R_min data from the complementary study by Yang et al. (2022).

3 Results

3.1 Soil LOC components in different habitat types

EOC varied in the range of 2.2–5.9 g C kg^‒1 in MFs, 2.7–8.3 g C kg^‒1 in SAs, and 3.1–6.9 g C kg^‒1 in APs (Fig.2). Overall, the mean (± SE) EOC content in SAs (5.1±0.3 g kg^‒1) was significantly larger than that in MFs (4.3±0.2 g C kg^‒1) (p<0.05), but similar to APs (4.8±0.2 g C kg^‒1) (p>0.05; Fig.2). The percentage of SOC attributed to EOC was 61.6% in MFs, 57.4% in SAs, and 60.1% in APs (Tab.1).

Fig.2 Box plots of (a) easily oxidizable carbon (EOC), (b) dissolved organic carbon (DOC), and (c) microbial biomass carbon (MBC) contents in the topsoil (0–20 cm) of mud flats (MFs), S. alterniflora marshes (SAs), and aquaculture ponds (APs) in 21 coastal wetlands in southeastern China (n = 63). Different lowercase letters above the boxplots within each panel indicate significant differences between habitat types (p<0.05).

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Tab.1 Different labile organic carbon components as percentages of soil organic carbon (SOC) across the three wetland habitat types.

Habitat types	EOC/SOC (%)	DOC/SOC (%)	MBC/SOC (%)
MFs	61.63 (3.49)	0.22 (0.02)	4.49 (0.48)
SAs	57.45 (5.00)	0.24 (0.03)	3.54 (0.50)
APs	60.09 (4.23)	0.23 (0.03)	4.49 (0.52)

Note: MFs, SAs, and APs represent mudflats, S. alterniflora marshes, and aquaculture ponds, respectively. EOC, DOC and MBC represent easily oxidizable carbon, dissolved organic carbon and microbial biomass carbon, respectively. SOC data are taken from Hong et al. (2023). The values in parentheses are standard errors.

The DOC content varied considerably between sites, ranging 8.1–29.3 mg C kg^‒1 in MFs, 10.5–78.3 mg C kg^‒1 in SAs, and 8.1–36.2 mg C kg^‒1 in APs (Fig.2). Overall, the mean DOC content (mean±SE) in SAs (22.2±2.3 mg C kg^‒1) was significantly higher than that in MFs (17.7±1.5 mg C kg^‒1) and APs (15.7±0.8 mg C kg^‒1) (p<0.001; Fig.2). The contributions of DOC to the total SOC were 0.22% in MFs, 0.24% in SAs, and 0.23% in APs (Tab.1).

MBC ranged 29.7‒800.5 mg C kg^‒1 in MFs, 36.4‒944.4 mg C kg^‒1 in SAs and 32.1‒1290.2 mg kg^‒1 in APs (Fig.2); the respective mean (±SE) values were 325.9±38.8 (MFs), 343.3±46.3 (SAs) and 389.1±59.7 (APs) mg C kg^‒1, without significant differences among habitat types (p>0.05; Fig.2). MBC accounted for 4.5% (MFs), 3.5% (SAs), and 4.5% (APs) of the total SOC (Tab.1).

3.2 Spatial variations of LOC components

There was a significant and positive latitudinal gradient in EOC (p<0.01; Fig.3‒Fig.3), and a negative latitudinal gradient in MBC across all three habitat types (p<0.01; Fig.3‒Fig.3). However, the relationships between latitude and DOC were weak and insignificant (p>0.05; Fig.3‒Fig.3).

Fig.3 Linear regressions between latitude and labile organic carbon components in the topsoil (0–20 cm) for the three habitat types. a, b, and c are EOC. d, e, and f are DOC. g, h, and i are MBC. a, d, and g are mudflats. b, e, and h are S. alterniflora marshes. c, f, and i are aquaculture ponds.

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3.3 Response of labile organic carbon to habitat modification

The relative responses (regarding RR₊₊ values) of soil labile organic carbon fractions (i.e., EOC, DOC and MBC) to habitat modification in coastal wetland are shown in Fig.4. In the case of transformation of MFs to SAs, EOC, DOC and MBC contents increased by approximately 18.6 % (Fig.4), 41.4 % (Fig.4) and 20.1 % (Fig.4), respectively. In contrast, conversion of SAs to APs decreased EOC and DOC contents by 5.9% (Fig.4) and 20.3% (Fig.4), respectively, but increased MBC contents by 25.5% (Fig.4).

Fig.4 Weighted response ratios (RR++) of (a) EOC, (b) DOC and (c) MBC contents in the topsoil (0‒20 cm) for the different habitat modification scenarios: MFs→SAs represents transformation from mudflats to S. alterniflora marshes; SAs→APs represents conversion from S. alterniflora marshes to aquaculture ponds. Bars represent the RR++ values and 95% CIs (n = 21 sampling sites). The asterisks (*) indicate significant differences from zero (p < 0.05).

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3.4 Environmental control of soil LOC components

The redundancy analysis (RDA) results show that TN, pH and C:N together explained 77.6% of the variations in LOC components in the MFs-to-SAs land cover change scenario (Fig.5). For SAs-to-APs conversion, changes in soil LOC components were strongly driven by TN, ${\text{SO}}_{\text{4}}^{\text{2}-}$, Clay and SWC, which together explained 86.6% of the variations (Fig.5).

Fig.5 Redundancy analysis (RDA) of the relationships between the EOC, DOC, MBC, SOC and the soil physicochemical properties in the topsoil (0–20 cm) for the different land cover change scenarios: (a) Transformation of mudflats to S. alterniflora marshes (MFs→SAs), and (b) Conversion of S. alterniflora marshes to aquaculture ponds (SAs→APs). The pie charts show the percentages of relative influence of the different soil physicochemical parameters on labile organic carbon (LOC).

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3.5 Relationships between LOC components and SOC mineralization

To explore the importance of soil LOC in driving SOC mineralization, we took R_min data from Yang et al. (2022) as the dependent variable and LOC component data from this study as the independent variables, and ran linear regressions between them. Across all sampling sites, R_min increased linearly with LOC components in the topsoil (p<0.05 or <0.01), with the most pronounced correlation observed for DOC, followed by EOC and MBC (Fig.6).

Fig.6 Linear regressions between SOC mineralization rate (Rmin) and (a) EOC, (b) DOC and (C) MBC contents in the topsoil (0–20 cm) of all sampling sites. Rmin data are taken from Yang et al. (2022). MFs, SAs and APs represent mud flats, S. alterniflora marshes and aquaculture ponds, respectively.

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4 Discussion

4.1 The effects of land use change on coastal wetland LOC

Coastal wetlands are one of the most fragile ecosystems and are very sensitive to climate and environmental changes (Xia et al., 2021). Their high productivity and water-logged conditions tend to favor the accumulation of labile organic carbon (LOC) that is vital to soil biogeochemical and ecological processes (Paterson and Sim, 2013; de Vries and Caruso, 2016). Many labile organic compounds, such as proteins, amino acids, amino sugars and urea, contain nitrogen (Farzadfar et al., 2021; Verrone et al., 2024), which may explain the strong influence of TN on the changes in LOC (Fig.5).

Soil LOC quantity and composition can be altered by land cover change, e.g., due to alien species invasion and land development (Deng et al., 2016; Zhang et al., 2018). Originally introduced to China in the 1970s to mitigate coastal erosion (Chung, 2006), the alien species S. alterniflora has since spread across the southeast coast of China and transformed many native mudflats into Spartina marshes (Meng et al., 2020). A recent study found that invasion by S. alterniflora enhanced the surface soil C stock of mudflats by 6.6 × 10⁶ g C ha^‒1 (Hong et al., 2023). Likewise, our results showed that the soil LOC components (EOC, DOC, and MBC) all increased significantly after Spartina invasion (Fig.2). Compared with bare mudflats, S. alterniflora can trap allochthonous organics with its aboveground biomass (Middelburg et al., 1997) and deposit labile organics through photosynthesis, root secretions and leaf littering (Zhang et al., 2010; Tong et al., 2011; Yang et al., 2016), thereby increasing EOC and DOC contents, which in turn would stimulate organotrophs such as bacteria and fungi, leading to higher MBC (Haynes, 2005; Xiao et al., 2015). Additionally, another study has shown that S. alterniflora increased the soil’s cation exchange capacity (Wang et al., 2016), which should also favor the sorption and retention of organics onto soil particles (Setia et al., 2013).

Soil EOC decreased slightly, and DOC decreased significantly after S. alterniflora marshes were converted into aquaculture ponds (Fig.2). This seems counter-intuitive because the frequent application of aquaculture feeds and deposition of animal wastes are expected to increase soil organic matter content (Lin and Lin, 2022). Nevertheless, the results agree with our other observations that both the total and labile organic nitrogen contents of the soil declined along with the transition from Spartina marshes to aquaculture ponds (Lin et al., 2023; Tan et al., 2024). Uprooting S. alterniflora to construct aquaculture ponds would have removed a major source of labile organics to the soil. In our study, the majority of aquaculture ponds are used for shrimp farming, characterized by a low feed conversion ratio, which would also minimize the amounts of unconsumed feed and animal waste going into the soil (Yang et al., 2021). Furthermore, during the non-farming season, the farmers often drain and dry the ponds, which could lead to further depletion of soil organic matters (Kauffman et al., 2018).

Unlike EOC and DOC, MBC was not affected significantly in either land cover change scenarios (Fig.2), likely because the microbial communities were able to exploit a broader range of substrates than LOC. Likewise, the relationship between SOC mineralization rate (R_min) and MBC (Fig.6) was the weakest (R² = 0.17), suggesting that not all of the soil microbes were involved in SOC mineralization. Being dissolved in the water, DOC would be most accessible to microbes, yielding the strongest relationship with R_min (R² = 0.49) despite its small contribution to the total SOC (Tab.1). In comparison, the weaker relationship with EOC (R² = 0.22) indicates a slightly lower accessibility of mineral-bound OC.

4.2 Latitudinal patterns among LOC components

Among the three LOC components, EOC was the overwhelming majority (Tab.1). An interesting observation is the positive latitudinal gradient in EOC that is consistent across habitat types (Fig.3‒Fig.3). We therefore reason that the gradient was not driven by habitat-specific properties; rather, it may reflect a common climate influence. For example, across the studied wetlands, the annual average air temperature varies from ~13 °C to >24 °C (Liu et al., 2003). The lower environmental temperatures at the higher latitudes may slow down microbial activities and turnover of EOC, which is consistent with observations in other systems (Garten, 2011; Wang et al., 2012) as well as our observed negative latitudinal gradient in MBC (Fig.3‒Fig.3). By comparison, there was no clear latitudinal trend in DOC (Fig.3‒Fig.3). We postulate that the dissolved nature of DOC would have allowed more frequent exchanges of DOC between the soil and the overlying water, effectively masking any temperature or latitudinal effects on DOC.

5 Conclusions

This study identified the impact patterns resulting from the invasion by S. alterniflora and its subsequent transformation into aquaculture ponds on LOC components in coastal wetland soil along China’s tropical-subtropical gradient. Our results showed that S. alterniflora’s encroachment on native mudflats elevated the soil levels of EOC and DOC, thereby increasing SOC mineralization rate. However, converting these areas into aquaculture ponds partially mitigated these changes. The observed opposite latitudinal gradients between EOC and MBC suggest temperature-dependent microbial turnover of EOC. As such, continuous global warming may accelerate EOC loss and microbial output of greenhouse gases.

Due to the necessity to avoid interference with the aquaculture operation, we were only able to sample the aquaculture ponds in the winter. By comparing the data across a broad latitudinal range, we were able to gain insights into climate effects on soil LOC. Nevertheless, biological activities are expected to increase in spring and summer, and therefore a more detailed understanding of seasonal variations in LOC will require repeated sampling on site in the future.

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Acknowledgements

This research was funded jointly by the Natural Science Foundation of Fujian Province, China (Grant Nos. 2022R1002006 and 2022R1002007), Graduate Innovation Foundation of School of Geographical Sciences, Fujian Normal University, the National Natural Science Foundation of China (Grant Nos. 42371100 and 41801070), and Henan Province Science Foundation for Youths of China (Grant Nos. 232300421256).

Conflict of interest

The authors declare that they have no conflict of interest.

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