Linking 3D Perinereis burrows with physicochemical factors on a tidal flat (Pearl River Delta, China)

ABSTRACT

This study employed a comprehensive approach involving field sampling, grain-size analysis, physicochemical measurements, CT scanning and three-dimensional reconstruction to investigate the intertidal flats of the Pearl River Delta (PRD). As Perinereis is an important bioindicator in relation to environmental factors, sedimentological and ichnological analyses were conducted at six of the 63 sampling stations. The aim was to characterize the composition and distribution of Perinereis traces, examine their relationships with physicochemical factors, including sediment grain size, salinity, turbidity, and total organic carbon (TOC) content, and further illustrate their environmental significance. The results showed that: (1) Perinereis traces consist predominantly of grazing and dwelling burrows. These burrows exhibit diverse morphologies, including simple cylindrical, Y-shaped, U-shaped, and complex branching networks, with some branches presenting swellings at junctions. (2) Salinity significantly influences Perinereis burrow diameter, showing a positive correlation in the low to moderate salinity range (0.28-3.97 PSU). Growth reaches a plateau when salinity exceeds a threshold of approximately 18 PSU, indicating a physiological tolerance limit. (3) Burrow diameter and sediment bioturbation exhibit no significant correlations with sediment grain size, salinity, turbidity, or TOC content. This may reflect infaunal interactions (e.g., associations with Macrophthalmus japonicus) and the combined influence of multiple environmental factors. This study improves our understanding of the biology and ichnology of modern Perinereis traces and provides a quantitative basis for interpreting interactions between infauna and their environment in intertidal flat ecosystems.

Keywords:
Deltaic tidal flat; Neoichnology; Perinereis; Physicochemical factors; Paleoenvironment

INTRODUCTION

Neoichnology focuses on interactions between modern organisms and sediments, integrating findings from biology, sedimentology, and paleontology (Adikaram et al., 2017; Brown et al., 2024; Dashtgard, 2011a, b; Knaust and Bromley, 2012; Kumar, 2017). It provides a theoretical framework for analyzing infauna and their burrowing behaviors, thereby facilitating an understanding of the dynamic relationships between infaunal activities and physicochemical factors. Studies of biogenic structures in modern tidal flats may reveal relationships between these structures and physicochemical conditions of coastal zones. Such studies may also help reconstruct sedimentary and environmental conditions during biological colonization by analyzing burrow characteristics (Benkhedda et al., 2021; Virtasalo et al., 2011). Particularly in estuarine tidal flats, bioturbation patterns typically reflect gradient changes in sediment grain size, salinity, and turbidity associated with freshwater input (Buatois et al., 2012, 2019; Demircan and Uchman, 2016; Morelle et al., 2024; Moyano et al., 2020; Sendra et al., 2019). Although considerable progress has been made in understanding these relationships over recent decades (Ayranci et al., 2014; Buatois and Mángano, 2011; Dashtgard, 2011a, b; Wang et al., 2019, 2024, 2025), further neoichnological studies of understudied taxa across diverse geographic regions are still needed, given the variability of trace makers and the complexity of environmental conditions.

The physicochemical gradients of deltaic tidal flats create a dynamic and highly stressful environment that exerts a strong selective influence on infaunal communities and their biogenic sedimentary structures (Passarelli et al., 2012, 2014). Polychaetes are fundamental bioturbators in such environments. Unlike predators or filter feeders, they can disrupt the chemical balance of sediments via feeding, digestion, excretion, and transporting sediments. They can also migrate through deep sediments, excrete nitrogen, and reconstruct microbial communities by transporting intestinal bacteria. These activities are crucial in driving sediment biogeochemical processes (Cournane et al., 2010; Fang et al., 2018; Koo and Seo, 2017). Previous studies have extensively investigated relationships between morphological characteristics of benthic organisms, the distribution of their burrows, and associated physicochemical factors. For instance, Wang et al. (2025) found that, in the Pearl River Delta (PRD), burrows of Macrophthalmus japonicus are more complex and bioturbation is more intense in environments with fine-grained substrates, high total organic carbon (TOC) content, freshwater to lower-mesohaline salinity, and suitable turbidity. Olabarria et al. (1998) observed that dominant bivalve organisms in the Rías Bajas in northwestern Spain are more prevalent in coarse sand and gravel substrates, as well as in the intertidal zone and in fine sand substrates containing 1-2% organic matter. Rowshan et al. (2023) showed that polychaete abundance and community dominance are greater in silty loam substrates, environments with high total organic matter (TOM) content, and high salinity in the shallow waters of the southern Caspian Sea, Iran. Species of Perinereis are widely distributed across the tidal-flat burrow systems in the PRD (Pang et al., 2021; Wang et al., 2019). However, research of their burrows in the PRD remain limited, particularly those involving systematic quantitative analyses of the relationships between burrow characteristics and environmental physicochemical factors. Consequently, Perinereis represents an ideal model organism for exploring how deltaic environments regulate biogenic sedimentary structures.

Traditional burrow-casting and excavation methods may damage or destroy the original burrow structure. However, computed tomography (CT) enables efficient analysis of complex burrow morphology, providing a reliable approach for linking bioturbation structures to physicochemical factors (Herringshaw et al., 2010; Howman et al., 2024; Mazik et al., 2008; Pennafirme et al., 2019). This study employed CT scanning and three-dimensional reconstruction to systematically and quantitatively analyze surface traces and morphological characteristics of Perinereis burrows in the tidal flats of the PRD. Specifically, this study aims to: (1) assess morphological and structural characteristics of Perinereis surface traces and dwelling burrows in the tidal flats of the PRD; (2) clarify the influence of physicochemical factors, including sediment grain size, salinity, turbidity, and TOC content, on burrow diameter and bioturbation activity; and (3) investigate patterns of Perinereis distribution under the comprehensive influence of multi-factor synergy and biological interactions.

STUDY AREA

Located along the northern coast of the South China Sea, the study area comprises the delta-plain tidal flats of the PRD in southern China and adjacent nearshore islands (Figures 1A-C). The complex river network of the PRD discharges an average annual water volume of approximately 2823×10⁸ m³ and a sediment load of 72.4×10⁶ t (Liu et al., 2014) into the South China Sea through eight estuarine outlets: Humen, Jiaomen, Hongqimen, Hengmen, Modaomen, Jitimen, Hutiaomen, and Yamen. All estuaries in the study area are tidally influenced and characterized by an irregular semidiurnal tidal cycle, with two flood tides and two ebb tides per day. Each lunar month includes six days of spring tides and six days of neap tides, with the remainder being intermediate tides. The tidal range generally varies from 0.86 m to 1.66 m, classifying the region as microtidal (Zhang et al., 2010, 2017). The study area lies south of the Tropic of Cancer and has a warm, humid subtropical monsoon climate. Average annual temperature ranges from 21.5-22.5°C, which meets the classification standard for a subtropical climate (annual average temperature ≥20°C). Sampling was conducted during winter, from December 2021 to February 2022. Average annual rainfall exceeds 1,600 mm (Wei et al., 2024), and there are pronounced seasonal variations in hydrological variables. Peaks in summer precipitation (900 ± 120 mm) and runoff (1.35 ± 0.20 × 10⁸ m³) occur first, followed by peaks in spring (350 ± 50 mm, 0.45 ± 0.08 × 10⁸ m³), autumn (250 ± 40 mm, 0.30 ± 0.07 × 10⁸ m³), and winter (100 ± 20 mm, 0.15 ± 0.05 × 10⁸ m³), in descending order (Li et al., 2020; Xiao and Cui, 2021). Precipitation is highly concentrated in summer, resulting in significant variability in river discharge and tidal currents. The wet season is characterized by strong hydrodynamics, enriched nutrients and frequent scouring of benthic organisms, whereas the dry season features weaker hydrodynamics, increased salinity and abundant aquatic vegetation (Feng et al., 2021; Pang et al., 2021; Yang et al., 2022). The bay contains numerous remnant hills and islands, which form natural barriers at the estuary mouths and effectively attenuate wave energy. Consequently, wave action is generally weak, with an average wave height of approximately 1 m (Jia et al., 2016). Intense weathering in the source regions supplies fine-grained sediments to the river systems. Total annual input of fine-grained sediment transported, deposited, and dispersed within the estuaries and adjacent coastal and shelf areas of the South China Sea exceeds 8400×10⁴ t (Chen et al., 2023).

Figure 1
Study area. (A) Map of China, red star marks the study area; (B) map of the Pearl River Delta; (C) satellite image showing the tidal flat that forms the study area (image source: http://glovis.usgs.gov/).

METHODS AND DATA

SAMPLING

Sampling was conducted using Qi’ao Island as the central reference point. Underwater sampling was performed along radial transects ranging from 12-20 km in length. A total of 63 sampling stations were established across the study area for sedimentological and ichnological analysis (Figure 2). Sediment samples were collected using PVC coring tubes measuring 15 cm in length and 7.5 cm in diameter. Areas showing visible signs of bioturbation were avoided during sampling. After collection, both ends of the cores were sealed to preserve burrow morphology. Surface sediments were collected at a depth of 0-5 cm below the sediment surface, and two parallel samples were prepared. These samples were sealed and stored in sterile polyethylene bags for subsequent analysis of indicators such as particle size and TOC. Two parallel surface-water samples were also collected and sealed in 100-ml plastic bottles for subsequent determination of salinity, turbidity, and related parameters. All samples were stored at ambient temperature in light-proof conditions to preserve their original composition before analysis. To obtain well-preserved and representative biogenic sedimentary structures, 15 cm-long PVC core tubes with an inner diameter of 7.5 cm were inserted into the sediment during low tide to collect samples in situ. The cores were then sealed within the tubes to maintain an anoxic environment that would effectively inhibit bioturbation. Based on the density of Perinereis burrows, 35 sediment cores were collected from 18 sampling stations. Six stations representing typical sedimentary environments inhabited by Perinereis were selected according to the distribution of tidal-flat microenvironments in the PRD. The locations of these stations were determined using a handheld GPS device and marked on Google Earth Pro. Columnar samples were collected to ensure adequate coverage of the different tidal-flat microenvironments while maintaining sample representativeness. Sampling focused on locations containing well-preserved and morphologically representative Perinereis burrows suitable for subsequent experiments such as CT scanning and three-dimensional reconstruction. The number of columnar samples collected and the specific coring points were mainly determined by the integrity of the preservation and representativeness of the Perinereis burrows, as well as the characteristics of microenvironmental disruption at each station. Only points with complete burrow morphology that were easy to collect and difficult to damage were sampled using PVC pipes.

Figure 2
Position of stations and surface-sediment distribution on the studied tidal flat of the Pearl River Delta; red stars mark stations where Perinereis burrows were present.

GRAIN SIZE ANALYSIS

A total of 58 surface sediment samples were collected from the 63 sampling stations for grain-size analysis (Table 1). Core samples were collected to a depth of 15 cm, with one or two cores collected at each station. For well-preserved and representative Perinereis burrows, additional directional core sampling was conducted using PVC pipes with diameters of 5 or 7.5 cm and a height of 15 cm. The sediment at station 63 consisted of gravel, while stations 17, 53, and 55 were characterized by coarse sand sediments, rendering them unsuitable for grain-size analytical instrumentation. Furthermore, sampling at station 43 was hindered by excessive current velocities, which prevented successful underwater sampling operations. All sediment samples were oven-dried at 105°C for 24 hours, and approximately 0.2 g of each sample was transferred to pre-cleaned glass beakers. To remove organic matter, 10% hydrogen peroxide (H₂O₂) was added, followed by 10% hydrochloric acid (HCl) to remove carbonates. Following chemical pretreatment, samples were left to settle. Before analysis, a 0.5% Calgon solution was added to disperse clay- and silt-sized particles, and the suspensions were ultrasonicated for 10 minutes (40 kHz) to ensure complete disaggregation. The grain-size test was performed using a Mastersizer 2000 (Malvern Instruments Ltd., Worcestershire, UK), with triplicate measurements performed for each sample to ensure reproducibility (Bertrand et al., 2014; Li et al., 2021; Song and Li, 2023).

Table 1
Grain-size parameters (mean grain size, standard deviation [SD], and skewness), turbidity (nephelometric turbidity units [NTU]), salinity (parts per thousand), and total organic carbon (TOC) content of samples collected from the Pearl River Delta.

Station	Mean Grain Size (mm)	SD (mm)	Skewness	Turbidity (NTU)	Salinity (PSU)	TOC (%)
1	0.37	0.64	0.12	8.36	30.10
2	0.35	0.68	0.02	8.15	31.80
3	0.39	0.61	0.10	7.45	31.80
4	0.01	0.32	0.12	12.02	12.90
5	0.02	0.16	-0.06	6.24	11.80	0.40
6	0.01	0.28	0.06	15.53	20.90	1.01
7	0.01	0.28	0.10	5.79	21.60	0.94
8	0.01	0.26	0.03	2.68	23.50	1.03
9	0.01	0.17	-0.23	10.65	26.90	0.85
10	0.26	0.52	0.26	40.32	28.11
11	0.01	0.24	0.05	45.88	11.80	1.03
12	0.01	0.29	0.13	6.40	18.30	1.16
13	0.01	0.22	-0.04	5.85	20.40	0.92
14	0.01	0.27	0.04	2.44	21.30	0.77
15	0.01	0.28	0.08	3.74	21.00	0.78
16	0.01	0.34	0.17	10.20	17.40	1.18
17				15.63	18.10	1.41
18	0.01	0.35	0.12	12.02	18.80	1.00
19	0.01	0.36	0.16	5.11	18.20	1.03
20	0.01	0.35	0.16	3.90	19.20	1.56
21	0.01	0.25	-0.01	6.94	18.60	1.04
22	0.01	0.20	-0.03	7.00	18.90	0.82
23	0.01	0.18	-0.08	2.69	20.70	0.25
24	0.05	0.18	0.59	3.33	22.00	0.20
25	0.01	0.22	0.07	1.67	22.30	0.57
26	0.01	0.25	-0.02	31.52	20.20	0.83
27	0.01	0.29	0.09	13.94	22.10	0.94
28	0.01	0.28	0.07	6.37	25.00	1.57
29	0.03	0.13	0.04	8.49	26.40	0.99
30	0.01	0.29	0.12	6.07	26.50	1.19
31	0.01	0.33	0.11	34.44	16.20	1.63
32	0.01	0.32	0.09	33.60	15.90	1.24
33	0.01	0.32	0.15	36.76	10.30	1.54
34	0.01	0.32	0.16	48.96	3.44	1.57
35	0.01	0.29	0.13	16.06	8.13	1.59
36	0.18	0.24	0.66	192.23	15.50
37	0.01	0.30	0.15	19.63	15.80	1.63
38	0.01	0.27	0.01	6.87	12.60	1.35
39	0.02	0.17	-0.02	5.01	9.31	0.55
40	0.02	0.19	0.06	58.74	14.30	2.18
41	0.02	0.17	-0.00	16.39	0.55	0.74
42	0.02	0.21	0.31	7.54	2.74	1.01
43					6.23
44	0.46	0.71	0.03	75.98	16.80
45	0.31	0.64	0.00	142.07	18.00	0.53
46	0.10	0.20	0.52	215.27	12.40	0.90
47	0.46	0.71	0.02	11.41	11.30
48	0.01	0.32	0.08	163.00	5.48	1.91
49	0.02	0.10	-0.31			1.50
50	0.36	0.68	0.02	148.03	13.90
51	0.31	0.62	0.02	11.38	10.60
52	0.25	0.61	0.02	113.90	14.10
53				192.57	13.60
54	0.25	0.58	-0.04	129.90	14.20
55				158.73	11.60
56	0.02	0.21	0.10	240.27	2.17	0.67
57	0.02	0.25	0.24	44.47	0.28	1.42
58	0.04	0.13	0.06	42.88	0.47	1.38
59	0.01	0.36	0.22	347.17	2.19	2.40
60	0.01	0.35	0.21	117.63	3.97	0.60
61	0.01	0.36	0.16	118.07	9.27	1.58
62	0.01	0.28	0.09	68.42	2.20	2.72
63				116.67	12.10	3.70

DETERMINATION OF TURBIDITY, SALINITY, AND ORGANIC MATTER CONTENT

Water samples were collected from 62 sampling stations during low tide for salinity and turbidity measurements. Stations 49 and 50 are hydrologically connected within the same water body; therefore, only Station 50 was sampled. Salinity was measured using an SX813 conductivity meter and recorded in Practical Salinity Units (PSU). Each sample was measured at least three times, and the average value was used to reduce the impact of instantaneous fluctuations and operational errors. The difference among the three readings was required to be less than 0.002 PSU. Turbidity was measured using an NS-type turbidity meter and expressed in nephelometric turbidity units (NTU). Each sample was measured at least three times, and the average value was used as the final result.

TOC content was analyzed in sediment samples collected from 48 stations (Table 1). Following Shetty and Goyal (2022), the loss-on-ignition (LOI) method was used to determine TOC content. The dried samples were ground using a mortar and pestle, further dried at 60 °C for 30 hours, and then heated at 550 °C for 4 hours. The weight loss resulting from organic matter combustion during LOI was measured using an electronic balance with a precision of ±0.001 g (Wang et al., 2025). Triplicate measurements were performed for each sample, with a relative standard deviation (RSD) < 5% ensuring analytical reproducibility.

COMPUTED TOMOGRAPHY (CT) SCANNING

All 35 collected cores were temporarily stored for one month under ambient-temperature, dry, and light-protected conditions. After completion of all field sampling, they were transported to the Nanjing Institute of Soil Research, Chinese Academy of Sciences, for CT scanning. During transport to the laboratory, all core tubes were maintained in a strictly upright position to prevent sediment disruption and resuspension. A Nanotom S CT scanner was employed with the following parameters: voltage 180 kV, power of 15 W, resolution of 200 nm (0.2 μm), and 3D magnification ranging from 1.5-100×. During scanning, the X-ray source emitted a collimated beam while the core was rotated 360° to acquire multi-angle projections of the specimen. A total of 4,575 projection images were collected per sample, with each 250 ms projection averaged over eight frames (two seconds per projection), totaling approximately 153 minutes per scan. Ring artifact correction was applied to improve image quality.

All three-dimensional reconstructions were completed at the Nanjing Institute of Geology and Paleontology, Chinese Academy of Sciences. To minimize file size and reduce computational demands, the reconstructed 3D volumes were converted to an 8-bit image format using Fiji-ImageJ software. Subsequently, the processed images were imported as a 3D project into VG Studio MAX (Version 2.1, Volume Graphics GmbH, Germany), in which a 3D non-linear digital median filter with edge-preserving properties was applied. This filter adopted a 5-voxel window size to mitigate image noise. The final scanned volumes exhibited a 3D voxel size of 30 µm. For sediment core samples, regions of interest (ROIs) containing burrow structures were segmented using a threshold-based seed-point-growing algorithm, which enabled the generation of a 3D visualization of the burrow network (Hale et al., 2015; Mimier and Żbikowski, 2017; Nel et al., 2001; Petrash et al., 2011).

NEOICHNOLOGICAL ASSESSMENT

According to field observations and CT image analysis, traces of biological disruption by Perinereis were found at only six of the 63 sampling stations (Table 2). At each station, five 1 m × 1 m quadrats were randomly excavated to a depth of 20 cm. To provide a physical reference scale, a ruler was placed on the sediment surface, after which photographs were taken to record burrow morphology. The average burrow density was determined by counting the number of trace producers and calculating the average. ImageJ software was then used to measure the diameter and cross-sectional area of individual burrows. The occupied surface area (cm²/m²) at each station was obtained by multiplying the average burrow density by the average total cross-sectional area. This value was then used to quantify the intensity of sediment bioturbation caused by Perinereis. According to Dashtgard (2011a), the sediment bioturbation rate (%) was calculated as (average burrow cross-sectional area × average burrow density) × 0.01. Additionally, the influence of physicochemical factors on average burrow diameter and their correlations were investigated. Logistic nonlinear least-squares regression was performed in Origin software to model the relationship between average burrow diameter and salinity. The significance of the model and its parameters was evaluated using ANOVA and t-tests, respectively. Goodness of fit was represented by R ² and adjusted R ² (P < 0.05).

Table 2
Quantification of Perinereis bioturbation: burrow morphometrics (diameter, cross-sectional area, and density) and calculated sediment disruption (%) across sampling stations in the Pearl River Delta.

Station	Average burrow diameter (cm)	Average burrow cross-sectional area (cm2)	Average burrow density (number of burrows/m2)	Cross-sectional area* burrow density (cm2/m2)	Sediment disruption (area)%
45	0.336	0.089	208	18.5	0.19
56	0.256	0.051	4900	250	2.50
57	0.102	0.008	300	2.4	0.02
58	0.157	0.019	7900	150	1.50
60	0.257	0.052	5100	265.2	2.65
62	0.353	0.098	2800	274.4	2.74

RESULTS

SEDIMENTOLOGY

Overall, Perinereis was predominantly found in fine-grained substrates, including silt, clay, and silty sand (Figure 2), all of which exhibit poor sorting (sorting index > 1; Figure 3).

Figure 3
Mean grain size and sorting values of all samples collected from the tidal flat; red stars indicate samples from stations where Perinereis was present.

The upper intertidal zone of the study area is characterized by poorly sorted muddy sediments, with arcuate ridge ripples (Figure 4A) and soft-sediment deformation structures. Dense reeds and shrubs surrounding the muddy tidal flat (Figure 4B) provide abundant organic matter for benthic organisms, leading to the formation of numerous burrow openings on the sediment surface.

Figure 4
Sedimentological features of the studied intertidal flat. (A) Curved ripple ridges in silty mud (station 53). (B) Mudflat with dense shrubs and reeds, featuring a high density of burrow openings (white arrows with black outline) (station 59). (C) Meandering tidal creeks (yellow arrows) traversing the intertidal flat, with numerous small water-filled pools (white arrows) on the surface of the middle intertidal flat (station 49). (D) Sandy parallel bedding (station 10). (E) Current ripples (station 45). (F) Oscillation ripples (outlined by a white dashed line) (station 2).

The middle intertidal zone mainly consists of poorly sorted silty sediments and is characterized by typical tidal bedding, including lenticular bedding, flaser bedding, and ripple cross-bedding. Meandering tidal creeks traverse the intertidal zone (Figure 4C) and transport fine-grained suspended sediments during flood tides. These sediments are subsequently deposited during ebb tides, forming extensive muddy deposits. Scattered shallow water-filled pools are also common in this zone.

The lower intertidal zone is characterized by well-sorted sandy sediments ranging from medium to fine sand (mean grain size: 0.1-0.5 mm). Various sedimentary structures occur in these sandy deposits, including parallel bedding (Figure 4D), trough cross-bedding, and current ripples (Figure 4E). Oscillation ripples were also clearly visible at the Dong’ao Island site (Figure 4F).

PHYSICOCHEMICAL FACTORS

The physicochemical factors measured included salinity, turbidity, and TOC content. Salinity gradually increases from west to east and decreases from south to north. Overall, the study area is dominated by saline and brackish-water environments, with only a few stations (41, 57, and 58) showing significantly lower salinity due to freshwater input from the land. According to salinity, the area can be divided into three categories: oligohaline (< 0.05 PSU), mesohaline (0.05-16 PSU), and polyhaline (> 16 PSU), with mean values and standard deviations of 0.38 ± 0.13, 9.68 ± 4.76, and 22.04 ± 4.40.

Turbidity can serve as an indicator of terrestrial inputs (e.g., riverine sediment transport) and hydrodynamic sorting processes. The waters of the study-area tidal flats are generally turbid, with turbidity gradually increasing from the sea toward the land (from east to west). However, no obvious systematic change is observed along the north-south transect (Figure 5B). According to turbidity, the water can be divided into four categories: <20 NTU, 20-80 NTU, 80-170 NTU, and >170 NTU. The corresponding mean values and standard deviations are 8.37 ± 4.57, 46.83 ± 14.11, 134.22 ± 19.23, and 237.50 ± 64.42.

Figure 5
Salinity (A) and turbidity (B) values measured at all stations on the Pearl River Delta tidal flat; red stars indicate stations where Perinereis was present.

TOC content ranges from 0.20% to 3.70%, with most stations falling within the 0.40%-2.00% range, indicating an overall low to moderate organic matter content. The highest TOC content (3.70%) occurs at station 63 and the lowest (0.20%) at station 24 (Table 1), reflecting significant spatial variability in organic matter enrichment. High TOC values are mostly found in areas strongly influenced by terrestrial inputs and characterized by relatively low salinities (2.17-14.30 PSU). In contrast, low TOC values are concentrated at stations 23 (0.25%) and 24 (0.20%), as well as at some high-salinity stations.

Analysis of the relationship between the burrow characteristics of Perinereis and environmental factors reveals a significant correlation between burrow diameter and salinity. Burrow diameter increases with rising salinity between 0.28 and 3.97 PSU, stabilizing above approximately 18 PSU (Figure 9). At salinities of 0.5-16 PSU, the degree of sediment bioturbation decreases as salinity increases (Figure 10D). However, neither burrow diameter nor sediment bioturbation shows a significant correlation with TOC content, mean grain size, or turbidity (Figures 10A-C).

NEOICHNOLOGY OF PERINEREIS

Surface traces and dwelling burrows constructed by Perinereis mainly occur in the modern intertidal zones of the PRD. Their detailed characteristics are described as follows.

Upper intertidal zone: On the sediment surface, Perinereis fecal pellets appear as slender, cylindrical, curved accumulations measuring approximately 1 mm in width (Figure 6D). Their burrow openings are predominantly circular (Figure 6C), measuring 0.5-2 mm in diameter, and may extend to depths of up to 11 cm below the surface (Figures 7A and 7B). The red and white arrows in Figure 7C indicate suspected dwelling/activity chambers. These burrows are relatively shallow, generally reaching only about 5 cm below the surface. Three-dimensional images show that Perinereis burrows consist mainly of fine, densely packed tunnels forming a highly interconnected network with extensive branching, bending, and bifurcation (typically at angles of 45-90°). The green arrows in Figures 7G and 7H show where tunnels intersect and intertwine. In contrast, Macrophthalmus japonicus burrows are mostly Y- or J-shaped, with thick main tunnels (5-10 mm in diameter) and multidirectional branches that form complex connected spaces (Figure 7C).

Figure 6
Traces of Perinereis on the sediment surface: surface crawling traces (red arrows) and openings of subsurface burrows (black arrows). (A) Red-colored Perinereis trace maker. (B) Burrow entrance of M. japonicus. (C) Burrow entrance of Perinereis. (D) Perinereis feces. (E) Crawling traces.

Figure 7
CT images of Perinereis from the Pearl River Delta intertidal flat. (A) and (B) Simple Perinereis burrows. (C) Simple, rarely branched, nearly vertical Perinereis burrows (red arrow) and simple J-shaped M. japonicus burrow (white arrow). (D) Simple Perinereis burrows (red arrow) and simple J-shaped M. japonicus burrows (white arrow). (E) Complex Perinereis burrows (red arrow) and simple Y-shaped M. japonicus burrows (white arrow). (F), (G), and (H) Complex Perinereis burrows with swellings (green arrow).

Middle intertidal zone: A live red Perinereis, measuring approximately 10-12 cm in length, was observed on the sediment surface (Figure 6A), alongside the circular 7-10 mm openings of adjacent Macrophthalmus japonicus burrows (Figure 6B). The two species often coexist at stations where Perinereis occurs, with Perinereis burrows frequently distributed around the Y-shaped burrows of Macrophthalmus japonicus (Figures 7D and 7E). Some Perinereis burrows are also Y-shaped and open upward, but they are smaller than the crab burrows. Three-dimensional images show that Perinereis burrows within the sediment are extremely dense (0.5-1 mm in diameter), with occasional swellings at branch points (Figure 7F, green arrow).

Lower intertidal zone: The substrate consists of sandy sediment mixed with fine gravel. Linear traces of Perinereis can be observed on the surface as slender features measuring approximately 2 mm in width (Figure 6E). Due to strong tidal and wave activity, bioturbation structures are poorly preserved, and Perinereis burrows and traces are relatively scarce.

Figures 8A and 8B show field observations of Perinereis burrows in sediments. Figures 8C and 8D are schematic diagrams of the corresponding morphologies. Simple burrows have few scattered branches and a relatively uniform diameter (Figure 8D). Their morphologies include U-shaped and Y-shaped structures. Complex burrows (Figure 8C) have numerous dense branches, expanded regions at bifurcations, and significant variations in burrow diameter. The combination of multiple U-shaped and Y-shaped branches, together with dense swollen areas, forms a complex three-dimensional network that supports the rapid movement and expanded foraging range of Perinereis within the sediment.

Figure 8
Comparison of dense (A) and sparse (B) Perinereis burrow openings on the Pearl River Delta tidal flat; comparison of complex (C) and simple (D) burrows.

DISCUSSION

Analysis of the sediment bioturbation caused by Perinereis (Table 2 and Figure 3) shows that this species inhabits fine-grained substrates and exhibits lower burrow density and weaker sediment bioturbation in coarser-grained sediments, such as those at Station 45. Perinereis can reduce the shear resistance of fine-grained sediments via setae movement and mucus lubrication, enabling efficient burrowing (Mimier and Żbikowski, 2017; Nel et al., 2001; Petrash et al., 2011). However, their limited muscle strength and mucus secretion make it difficult to penetrate medium and coarse sands (Francoeur and Dorgan, 2014; Sun et al., 2019), resulting in a significant reduction in burrowing ability. The surface tension of fine-grained substrates is low and burrow stability is poor, suggesting that Perinereis may rely on the stable burrow structures of Macrophthalmus japonicus for survival (Ho et al., 1997; Palomo et al., 2004). However, the bioturbation activities of Perinereis can increase sediment porosity, improve the distribution of organic matter, promote microbial activity, and indirectly provide Macrophthalmus japonicus with more benthic microalgae or organic detritus (Alvarez et al., 2018; Palomo et al., 2004; Patel and Desai, 2009). This is consistent with observations from Stations 58, 60, and 62, where the two species often co-occur. Together with the burrow-characteristic data presented in Table 3, these findings suggest that suitable environmental conditions and infaunal interactions can improve the settlement success of Perinereis and promote the formation of complex burrows. To a certain extent, this can also weaken the direct control of sediment grain size on burrow density (Kruger and Woodin, 1993; Palomo and Iribarne, 2000).

Table 3
Characteristics of simple and complex burrows across all Perinereis stations based on CT images.

Station	Morphological structure	Swelling status	Symbiotic relationship	Burrow type
45	Vertical tubular	No swelling	None	Simple
56	Vertical tubular and Y-shaped	No swelling	None	Simple
57	Vertical tubular and Y-shaped	No swelling	None	Simple
58	Vertical tubular, U-shaped and Y-shaped, multiple branches	With swelling	Associated with M. japonicus	Complex
60	Vertical tubular, U-shaped and Y-shaped	No swelling	Associated with M. japonicus	Simple
62	Vertical tubular, U-shaped and Y-shaped, multiple branches	With swelling	Associated with M. japonicus	Complex

Salinity is an important factor affecting the growth and development of infauna. It can also induce spatial heterogeneity by influencing infaunal behavior and distribution (Ayranci & Dashtgard, 2013, 2016; Freitas et al., 2015; Gingras et al., 2011; La Croix et al., 2015). In environments with fluctuating salinity, Perinereis must maintain homeostasis via ion and osmotic regulation. Figure 9A shows an overall positive correlation between salinity and individual burrow diameter, with each burrow acting as a statistical unit. Data dispersion at a given salinity reflects individual differences: each salinity value in the figure corresponds to a single sampling station, and the shape and color of the data points distinguish burrow-diameter measurements from different stations. The widest distribution of burrow diameters occurs at a salinity of 2.20 PSU, which also has the largest number of data points. This is because low-salinity tidal-flat areas are characterized by high organic matter content, abundant food resources, and relatively low predation levels. Together, these factors promote faster growth, larger body size in Perinereis individuals, and increased variability in burrow diameter. As salinity increases, increased osmotic stress may inhibit growth. However, Perinereis tends to develop more advanced tissue structures to meet its physiological requirements. This results in an increase in individual diameter, showing characteristics of compensatory growth (Lv et al., 2017; Fang et al., 2016). Figure 9B uses the average burrow diameter at each station as the statistical unit. Fitted using a logistic model, it reveals a nonlinear saturation relationship between salinity and average burrow diameter, characterized by rapid growth at low salinity and stabilization at high salinity. Under low- to moderate-salinity conditions (0.28-3.97 PSU), average burrow diameter increases with rising salinity, which is consistent with previous studies (Gingras et al., 2008, 2024). When salinity exceeds 18 PSU (e.g., at station 45), the diameter tends to stabilize, indicating that Perinereis has reached its physiological salinity tolerance limit (Feng et al., 2014). Regression analysis showed that the model had an R² of 0.84, an adjusted R² of 0.59, an ANOVA F-value of 24.69, and a P-value of 0.0391 (< 0.05), indicating that the model was significantly effective overall.

Figure 9
Relationship between burrow diameter (cm) and salinity (PSU) at sampling stations where Perinereis was present. (A) Scatter plot of the diameters of multiple burrows at Perinereis sampling stations under different salinity conditions. (B) Linear regression showing the relationship between salinity and average burrow diameter.

The characteristics of tidal-flat bioturbation are collectively regulated by sediment grain size, turbidity, and TOC content (Grandjean et al., 2024; Li et al., 2019; Nauta et al., 2024). High turbidity is often associated with high sedimentation rates, and the deposition of fine flocculated particles can clog the filter-feeding structures of Perinereis, significantly affecting its activities. At the same time, reduced transparency inhibits phytoplankton photosynthesis, resulting in decreased primary productivity (Cloern, 1987; Davies-Colley and Smith, 2001). The TOC content of a sedimentary environment can be used to characterize its nutritional status, food availability, environmental stability, and habitat suitability (Hyland et al., 2005; Li et al., 2016). Although TOC is related to food availability, this relationship is neither absolute nor precise, and TOC can only be used as an indicator of potential food sources. TOC includes both easily decomposable and refractory components, and total TOC does not directly reflect the amount of active organic carbon available to infauna. This study suggests that only the easily decomposable components of TOC serve as effective carbon and food sources for Perinereis (Li et al., 2022; Wang et al., 2024). Analysis of six stations where Perinereis occurred in the intertidal zone of the PRD showed no significant correlation between physicochemical factors and bioturbation intensity. This differs from the traditional view of multi-factor synergistic regulation. However, this conclusion is limited by the regional sedimentary environment and sample size, and is therefore mainly applicable to the study area. Spearman’s rank correlation analysis using Origin software (N = 6) revealed that only mean grain size was strongly negatively correlated with bioturbation rate (r _s = -0.74, P = 0.09). While this relationship did not reach the significant level of P<0.05, the result at P<0.1 indicates a tendency for bioturbation rate to decrease with increasing mean grain size. Correlations between bioturbation rate and TOC (r_s=0.20, P=0.70), turbidity (r _s =0.37, P=0.47), and salinity (r _s =0.37, P=0.47) were weak and not statistically significant. Overall, mean grain size exhibited the strongest relationship with bioturbation intensity, while the regulatory effect of other factors is insignificant (Figures 10A-D). This may be related to infaunal dependence on sediment physical characteristics. Fine-grained sediments facilitate drilling and the stability of dwelling tubes, thereby enhancing sediment bioturbation intensity. Conversely, the loose structure of coarse-grained sediments is not conducive to burrow maintenance, leading to reduced bioturbation rates (Ho et al., 1997). Therefore, mean grain size is the main factor affecting disruption behavior, with the roles of TOC, turbidity, and salinity being relatively indirect or offset by flexible feeding strategies (Dorgan et al., 2008).

Figure 10
Relationship between TOC content (A), mean grain size (B), turbidity (C), salinity (D), and sediment disruption at stations where Perinereis was present on the Pearl River Delta tidal flats. Red stars indicate sediment disruption at stations where Perinereis was present.

As typical biogenic traces, the burrows of the polychaete Perinereis preserve behavioral responses to environmental conditions (Kulkarni and Panchang, 2015). Burrow density is sensitive to population dynamics and short-term catastrophic events; a sudden decrease may indicate population collapse caused by anoxia, toxic pulses, or rapid sediment burial (Bromley and Ekdale, 1984; Dworschak and Rodrigues, 1997; Martin, 2004). Burrow diameter reflects individual physiological and behavioral adjustments and may indicate chronic, sublethal environmental stressors (Blankson et al., 2017; Koo and Seo, 2017; Rodríguez-Tovar et al., 2014; Tian et al., 2019).

CONCLUSIONS

This study examined the burrow systems of Perinereis in the intertidal zones of the PRD, China. The results suggest that Perinereis burrows exhibit a wide range of morphologies, including simple cylindrical, Y-shaped, U-shaped, and complex reticulated structures, with local swellings occasionally occurring at branch points. This morphological variation reflects the organism’s ability to flexibly adjust its behavioral patterns in response to local microenvironmental conditions. Salinity was identified as the environmental factor most strongly correlated with burrow diameter, exhibiting a nonlinear saturating relationship: low to moderate salinity promotes burrow enlargement, whereas burrow diameter tends to stabilize at high salinity levels approaching the species’ physiological tolerance limit. However, salinity had no significant effect on burrow density.

Neither burrow diameter nor sediment bioturbation showed a significant correlation with individual factors such as sediment grain size, salinity, turbidity, or TOC content. This suggests that these parameters are jointly regulated by biotic interactions and multiple environmental factors. The bioturbation rate was strongly negatively correlated with mean grain size, indicating that mean grain size is the primary factor controlling Perinereis bioturbation behavior. The influences of TOC, turbidity, and salinity appear to be relatively indirect or may be offset by the flexible feeding strategies of infaunal organisms.

In terms of potential paleoenvironmental implications, the morphology of Perinereis burrows may indicate low-energy, nutrient-rich microenvironments in ancient intertidal zones. Differential responses in burrow density and diameter may reflect population dynamics and long-term environmental stress in paleo-ecosystems, providing preliminary insights for future paleoenvironmental reconstruction studies.

DATA AVAILABILITY STATEMENT

The authors confirm that all relevant data utilized in this study are included within the article.

SUPPLEMENTARY MATERIAL

No relevant information.

ACKNOWLEDGMENTS

We thank Dr. Rubens Lopes, editor-in-chief of Ocean and Coastal Research, the associate editor, and two anonymous reviewers for their valuable and constructive comments over the past year, which were essential to the completion of this manuscript. We also acknowledge Dr. Chen Jie for CT scanning technical support at the laboratory of the Nanjing Institute of Soil Research, Chinese Academy of Sciences, and Dr. Yin Zongjun and Ms. Wu Suping for three-dimensional visualization at the laboratory of the Nanjing Institute of Geology and Paleontology, Chinese Academy of Sciences.

REFERENCES

• Adikaram, M., Pitawala, A., Ishiga, H. & Jayawardhana, D. 2017. Paleoenvironmental reconstruction of quaternary sedimentation in eastern Sri Lanka: an ichnological study. Journal Geological Society Of India, 89(1), 71-76. DOI: https://doi.org/10.1007/s12594-017-0560-8
  » https://doi.org/10.1007/s12594-017-0560-8
• Alvarez, M.F., Bazterrica, M.C., Fanjul, E., Addino, M.S., Valiñas, M.S., Iribarne, O.O. & Botto, F. 2018. Effects of two estuarine intertidal polychaetes on infaunal assemblages and organic matter under contrasting crab bioturbation activity. Journal of Sea Research, 139, 33-40. DOI: https://doi.org/10.1016/j.seares.2018.06.008
  » https://doi.org/10.1016/j.seares.2018.06.008
• Ayranci, K., Dashtgard, S.E. & MacEachern, J.A. 2014. A quantitative assessment of the neoichnology and biology of a delta front and prodelta, and implications for delta ichnology. Palaeogeography, Palaeoclimatology, Palaeoecology, 409, 114-134. DOI: https://doi.org/10.1016/j.palaeo.2014.05.013
  » https://doi.org/10.1016/j.palaeo.2014.05.013
• Ayranci, K. & Dashtgard, S.E. 2013. Infaunal holothurian distributions and their traces in the Fraser River delta front and prodelta, British Columbia, Canada. Palaeogeography, Palaeoclimatology, Palaeoecology , 392, 232-246. https://doi.org/10.1016/j.palaeo.2013.09.021
  » https://doi.org/10.1016/j.palaeo.2013.09.021
• Ayranci, K. & Dashtgard, S.E. 2016. Asymmetrical deltas below wave base: insights from the Fraser River Delta, Canada. Sedimentology, 63(3), 761-779. DOI: https://doi.org/10.1111/sed.12237
  » https://doi.org/10.1111/sed.12237
• Benkhedda, A., Defaflia, N., Cherif, A., Naimi, M.N., Mazouz, E.-H. & Palma-Ramírez, A. 2021. Shallow marine trace fossils from the Middle Miocene of the Tebessa Basin (NE Algeria) and their palaeonvironmental implications. Revista Brasileira de Paleontologia, 24(4), 323-335. DOI: https://doi.org/10.4072/rbp.2021.4.03
  » https://doi.org/10.4072/rbp.2021.4.03
• Bertrand, S., Daga, R., Bedert, R. & Fontijn, K. 2014. Deposition of the 2011-2012 Cordón Caulle tephra (Chile, 40°S) in lake sediments: implications for tephrochronology and volcanology. Journal of Geophysical Research: Earth Surface, 119(12), 2555-2573. DOI: https://doi.org/10.1002/2014jf003321
  » https://doi.org/10.1002/2014jf003321
• Blankson, E.R., Adhikary, N.R.D. & Klerks, P.L. 2017. The effect of lead contamination on bioturbation by Lumbriculus variegatus in a freshwater microcosm. Chemosphere, 167, 19-27. DOI: https://doi.org/10.1016/j.chemosphere.2016.09.128
  » https://doi.org/10.1016/j.chemosphere.2016.09.128
• Bromley, R.G. & Ekdale, A.A. 1984. Chondrites: a trace fossil indicator of anoxia in sediments. Science, 224(4651), 872-874. DOI: https://doi.org/10.1126/science.224.4651.872
  » https://doi.org/10.1126/science.224.4651.872
• Brown, D., Corlett, H., Kibblewhite, T., Whitaker, F., Zonneveld, J.-P. & Gingras, M. 2024. Neoichnology of a microtidal carbonate intertidal zone: Abu Dhabi, UAE. Palaios, 39(9), 344-361. DOI: https://doi.org/10.2110/palo.2023.042
  » https://doi.org/10.2110/palo.2023.042
• Buatois, L.A. & Mángano, M.G. 2011. Ichnology: organism-substrate interactions in space and time. Cambridge, Cambridge University Press.
• Buatois, L.A., Mángano, M.G. & Pattison, S.A.J. 2019. Ichnology of prodeltaic hyperpycnite-turbidite channel complexes and lobes from the Upper Cretaceous Prairie Canyon Member of the Mancos Shale, Book Cliffs, Utah, USA. Sedimentology , 66(5), 1825-1860. DOI: https://doi.org/10.1111/sed.12560
  » https://doi.org/10.1111/sed.12560
• Buatois, L.A., Santiago, N., Herrera, M., Plink-Björklund, P., Steel, R., Espin, M. & Parra, K. 2012. Sedimentological and ichnological signatures of changes in wave, river and tidal influence along a Neogene tropical deltaic shoreline. Sedimentology , 59(5), 1568-1612. DOI: https://doi.org/10.1111/j.1365-3091.2011.01317.x
  » https://doi.org/10.1111/j.1365-3091.2011.01317.x
• Chen, Y., Deng, B., Saito, Y., Wang, Z., Yang, X. & Wu, J. 2023. Pearl River sediment dispersal over its associated delta-estuary-shelf system during the Holocene. Sedimentology , 70(7), 2331-2354. DOI: https://doi.org/10.1111/sed.13123
  » https://doi.org/10.1111/sed.13123
• Cloern, J.E. 1987. Turbidity as a control on phytoplankton biomass and productivity in estuaries. Continental Shelf Research, 7(11-12), 1367-1381. DOI: https://doi.org/10.1016/0278-4343(87)90042-2
  » https://doi.org/10.1016/0278-4343(87)90042-2
• Cournane, S., León Vintró, L. & Mitchell, P.I., 2010. Modelling the reworking effects of bioturbation on the incorporation of radionuclides into the sediment column: implications for the fate of particle-reactive radionuclides in Irish Sea sediments. Journal of Environmental Radioactivity, 101(11), 985-991. DOI: https://doi.org/10.1016/j.jenvrad.2010.07.006
  » https://doi.org/10.1016/j.jenvrad.2010.07.006
• Dashtgard, S.E. 2011a. Linking invertebrate burrow distributions (neoichnology) to physicochemical stresses on a sandy tidal flat: implications for the rock record. Sedimentology , 58(6), 1303-1325. DOI: https://doi.org/10.1111/j.1365-3091.2010.01210.x
  » https://doi.org/10.1111/j.1365-3091.2010.01210.x
• Dashtgard, S.E. 2011b. Neoichnology of the lower delta plain: Fraser River Delta, British Columbia, Canada: Implications for the ichnology of deltas. Palaeogeography Palaeoclimatology Palaeoecology, 307(1-4), 98-108. DOI: https://doi.org/10.1016/j.palaeo.2011.05.001
  » https://doi.org/10.1016/j.palaeo.2011.05.001
• Davies‐Colley, R.J. & Smith, D.G. 2001. Turbidity suspeni) ed sediment, and water clarity: a review 1. JAWRA Journal of the American Water Resources Association, 37(5), 1085-1101. DOI: https://doi.org/10.1111/j.1752-1688.2001.tb03624.x
  » https://doi.org/10.1111/j.1752-1688.2001.tb03624.x
• Demircan, H. & Uchman, A. 2016. Ichnology of prodelta deposits of the Mezardere Formation (late Eocene-early Oligocene) in the Gökçeada island, western Turkey. Geodinamica Acta, 28(1-2), 86-100. DOI: https://doi.org/10.1080/09853111.2015.1113720
  » https://doi.org/10.1080/09853111.2015.1113720
• Dorgan, K.M., Arwade, S.R. & Jumars, P.A. 2008. Worms as wedges: effects of sediment mechanics on burrowing behavior. Journal of Marine Research, 66, 219-254.
• Dworschak, P.C. & Rodrigues, S.A. 1997. A modern analogue for the trace fossil Gyrolithes: burrows of the thalassinidean shrimp Axianassa australis. Lethaia, 30(1), 41-52. DOI: https://doi.org/10.1111/j.1502-3931.1997.tb00443.x
  » https://doi.org/10.1111/j.1502-3931.1997.tb00443.x
• Fang, J., Zhang, J., Jiang, Z., Du, M., Liu, Y., Mao, Y., Gao, Y. & Fang, J., 2016. Environmental remediation potential of Perinereis aibuhitensis (Polychaeta) based on the effects of temperature and feed types on its carbon and nitrogen budgets. Marine Biology Research, 12(6), 583-594. DOI: https://doi.org/10.1080/17451000.2016.1177653
  » https://doi.org/10.1080/17451000.2016.1177653
• Fang, J., Jiang, Z., Fang, J., Kang, B., Gao, Y. & Du, M. 2018. Selectivity of Perinereis aibuhitensis (Polychaeta, Nereididae) feeding on sediment. Marine Biology Research , 14(5), 478-483. DOI: https://doi.org/10.1080/17451000.2018.1426864
  » https://doi.org/10.1080/17451000.2018.1426864
• Feng, S., Huang, G., Lai, Z., Liang, W., Wu, M., Tang, L. & Pan, Y. 2014. Tolerance studies on the temperature, salinity and desiccation in Perinereis aibuhitensis. Transactions of Oceanology and Limnology, 1, 109-114.
• Feng, X., Zhang, W., Zhu, Z., Chevuturi, A. & Chen, W. 2021. Variability and changes in Pearl River Delta water level: oceanic and atmospheric forcing perspectives. Journal of Hydrometeorology, 22(9), 2407-2422. DOI: https://doi.org/10.1175/JHM-D-21-0037.1
  » https://doi.org/10.1175/JHM-D-21-0037.1
• Francoeur, A.A. & Dorgan, K.M. 2014. Burrowing behavior in mud and sand of morphologically divergent polychaete species (Annelida: Orbiniidae). The Biological Bulletin, 226(2), 131-145. DOI: https://doi.org/10.1086/bblv226n2p131
  » https://doi.org/10.1086/bblv226n2p131
• Freitas, R., Pires, A., Velez, C., Almeida, Â., Wrona, F.J., Soares, A.M.V.M. & Figueira, E. 2015. The effects of salinity changes on the Polychaete Diopatra neapolitana: Impacts on regenerative capacity and biochemical markers. Aquatic Toxicology, 163, 167-176. DOI: https://doi.org/10.1016/j.aquatox.2015.04.006
  » https://doi.org/10.1016/j.aquatox.2015.04.006
• Gingras, M.K., Dashtgard, S.E., MacEachern, J.A. & Pemberton, S.G. 2008. Biology of shallow marine ichnology: a modern perspective. Aquatic Biology, 2, 255-268. DOI: https://doi.org/10.3354/ab00055
  » https://doi.org/10.3354/ab00055
• Gingras, M.K., MacEachern, J.A., Dashtgard, S.E. 2011. Process ichnology and the elucidation of physico-chemical stress. Sedimentary Geology, 237(3-4), 115-134. DOI: https://doi.org/10.1016/j.sedgeo.2011.02.006
  » https://doi.org/10.1016/j.sedgeo.2011.02.006
• Gingras, M.K., MacEachern, J.A., Dashtgard, S.E. & Bann, K.L., 2024. The Teichichnus Ichnofacies: its neoichnological basis and identification in the rock record. Sedimentology , 72(2), 408-441. DOI: https://doi.org/10.1111/sed.13246
  » https://doi.org/10.1111/sed.13246
• Grandjean, T.J., Weenink, R., van der Wal, D., Addink, E.A., Hu, Z., Liu, S., Wang, Z.B., Yuan, L. & Bouma, T.J. 2024. Critical turbidity thresholds for maintenance of estuarine tidal flats worldwide. Nature Geoscience, 17(6), 539-544. DOI: https://doi.org/10.1038/s41561-024-01431-3
  » https://doi.org/10.1038/s41561-024-01431-3
• Hale, R., Boardman, R., Mavrogordato, M.N., Sinclair, I., Tolhurst, T.J. & Solan, M. 2015. High-resolution computed tomography reconstructions of invertebrate burrow systems. Scientific Data, 2, 150052. DOI: https://doi.org/10.1038/sdata.2015.52
  » https://doi.org/10.1038/sdata.2015.52
• Herringshaw, L.G., Sherwood, O.A. & McIlroy, D. 2010. Ecosystem engineering by bioturbating polychaetes in event bed microcosms. Palaios , 25(1), 46-58. DOI: https://doi.org/10.2110/palo.2009.p09-055r
  » https://doi.org/10.2110/palo.2009.p09-055r
• Ho, K.K., Kyoo, Y.S. & Jin, C.Y. 1997. Sediment preference and burrow shape of the polychaete, Perinereis aibuhitensis according to the laboratory culture. Korean Journal of Fisheries and Aquatic Sciences, 30(4), 634-639.
• Howman, R.M., Mavrogordato, M.N., Alverez-Borges, F. & Solan, M. 2024. Computed tomography reconstructions of burrow networks for the Opheliid polychaete, Armandia cirrhosa. Scientific Data , 11(1), 695. DOI: https://doi.org/10.1038/s41597-024-03557-w
  » https://doi.org/10.1038/s41597-024-03557-w
• Hyland, J., Balthis, L., Karakassis, I., Magni, P., Petrov, A., Shine, J., Vestergaard, O. & Warwick, R. 2005. Organic carbon content of sediments as an indicator of stress in the marine benthos. Marine Ecology Progress Series, 295, 91-103. DOI: https://doi.org/10.3354/meps295091
  » https://doi.org/10.3354/meps295091
• Jia, P., Xia, Z., Yin, Y. & Xue, Q. 2016. Lingdingyang Bay, Pearl River Estuary (China): geomorphological evolution and hydrodynamics. Geological Society, London, Special Publications, 429, 171-184. DOI: https://doi.org/10.1144/SP429.14
  » https://doi.org/10.1144/SP429.14
• Knaust, D. & Bromley, R.G. 2012. Trace fossils as indicators of sedimentary environments. Amsterdam, Elsevier.
• Koo, B.J. & Seo, J. 2017. Sediment reworking by a polychaete, Perinereis aibuhitensis, in the intertidal sediments of the Gomso Bay, Korea. Ocean Science Journal, 52(4), 511-518. DOI: https://doi.org/10.1007/s12601-017-0037-0
  » https://doi.org/10.1007/s12601-017-0037-0
• Kruger, C.D. & Woodin, S.A. 1993. Spatial persistence and sediment disturbance of an arenicolid polychaete. Limnology and Oceanography, 38(3), 509-520. DOI: https://doi.org/10.4319/lo.1993.38.3.0509
  » https://doi.org/10.4319/lo.1993.38.3.0509
• Kulkarni, K.G. & Panchang, R. 2015. New insights into polychaete traces and fecal pellets: another complex ichnotaxon?. PLOS One, 10(10), e0139933. DOI: https://doi.org/10.1371/journal.pone.0139933
  » https://doi.org/10.1371/journal.pone.0139933
• Kumar, A. 2017. Recent biogenic traces from the coastal environments of the southern Red Sea coast of Saudi Arabia. Arabian Journal of Geosciences, 10(22), 500. DOI: https://doi.org/10.1007/s12517-017-3293-5
  » https://doi.org/10.1007/s12517-017-3293-5
• La Croix, A.D., Dashtgard, S.E., Gingras, M.K., Hauck, T.E. & MacEachern, J.A., 2015. Bioturbation trends across the freshwater to brackish-water transition in rivers. Palaeogeography, Palaeoclimatology, Palaeoecology , 440, 66-77. https://doi.org/10.1016/j.palaeo.2015.08.030
  » https://doi.org/10.1016/j.palaeo.2015.08.030
• Li, D., Liu, X., Liu, Z. & Zhao, X. 2016. Variations in total organic carbon and acid-volatile sulfide distribution in surface sediments from Luan River Estuary, China. Environmental Earth Sciences, 75(14), 1073. DOI: https://doi.org/10.1007/s12665-016-5873-1
  » https://doi.org/10.1007/s12665-016-5873-1
• Li, J., Hu, R., Guo, Y., Chen, S., Xie, X., Qin, J.G., Ma, Z., Zhu, C. & Pei, S. 2019. Bioturbation of peanut worms Sipunculus nudus on the composition of prokaryotic communities in a tidal flat as revealed by 16S rRNA gene sequences. MicrobiologyOpen, 8(8), e00802. DOI: https://doi.org/10.1002/mbo3.802
  » https://doi.org/10.1002/mbo3.802
• Li, J., Shi, X., Chen, Y.D. & Zhang, L. 2020. Proposing a trend-based time-varying approach to assess climate- and human-induced impacts on streamflow. Hydrological Sciences Journal, 65(12), 2043-2056. DOI: https://doi.org/10.1080/02626667.2020.1785625
  » https://doi.org/10.1080/02626667.2020.1785625
• Li, L., Dai, M., Zhao, Y.-C., Chen, Y.-S., Xu, C.-l., Wang, S.-J. & Jiang, M. 2022. Study on integrated bioremediation of Suaeda glauca and Perinereis aibuhitensis on Meretrix meretrix aquaculture ponds. Marine Fisheries, 44(4), 480-490. DOI: https://doi.org/10.13233/j.cnki.mar.fish.2022.04.006
  » https://doi.org/10.13233/j.cnki.mar.fish.2022.04.006
• Li, Z., Wang, X., Vandenberghe, J. & Lu, H. 2021. Extension of the Upper Yellow River into the Tibet Plateau: review and new data. Quaternary, 4(2), 14. DOI: https://doi.org/10.3390/quat4020014
  » https://doi.org/10.3390/quat4020014
• Liu, F., Yuan, L., Yang, Q., Ou, S., Xie, L. & Cui, X. 2014. Hydrological responses to the combined influence of diverse human activities in the Pearl River delta, China. Catena, 113, 41-55. DOI: https://doi.org/10.1016/j.catena.2013.09.003
  » https://doi.org/10.1016/j.catena.2013.09.003
• Lv, F., Nie, Q., Yu, Y., Liu, F., Lv, L. & Zhao, W., 2017. Effect of salinity on the growth performance, body composition, antioxidant indexes of Perinereis aibuhitensis and total nitrogen in the substrate. Agricultural Sciences, 8(11), 1239-1252. DOI: https://doi.org/10.4236/as.2017.811089
  » https://doi.org/10.4236/as.2017.811089
• Martin, K.D. 2004. A re-evaluation of the relationship between trace fossils and dysoxia. Geological Society, London, Special Publications , 228(1), 141-156. DOI: https://doi.org/10.1144/GSL.SP.2004.228.01.08
  » https://doi.org/10.1144/GSL.SP.2004.228.01.08
• Mazik, K., Curtis, N., Fagan, M.J., Taft, S. & Elliott, M. 2008. Accurate quantification of the influence of benthic macro- and meio-fauna on the geometric properties of estuarine muds by micro computer tomography. Journal of Experimental Marine Biology and Ecology, 354(2), 192-201. DOI: https://doi.org/10.1016/j.jembe.2007.11.006
  » https://doi.org/10.1016/j.jembe.2007.11.006
• Mimier, D. & Żbikowski, J. 2017. Effect of substrate change on macrozoobenthos structure. Ecological Questions, 27, 109-118. DOI: https://doi.org/10.12775/eq.2017.032
  » https://doi.org/10.12775/eq.2017.032
• Morelle, J., Huguet, A., Richard, A., Laverman, A.M., Roose-Amsaleg, C., Parlanti, E., Sourzac, M., Mesnage, V., Lecoq, N., Deloffre, J., Viollier, E., Maire, O. & Orvain, F. 2024. Antagonistic impacts of benthic bioturbator species: interconnected effects on sedimentary properties, biogeochemical variables, and microbial dynamics. Journal of Experimental Marine Biology and Ecology , 573, 152000. DOI: https://doi.org/10.1016/j.jembe.2024.152000
  » https://doi.org/10.1016/j.jembe.2024.152000
• Moyano Paz, D., Richiano, S., Varela, A.N., Gómez Dacál, A.R. & Poiré, D.G. 2020. Ichnological signatures from wave- and fluvial-dominated deltas: The LA Anita formation, upper Cretaceous, austral-magallanes basin, Patagonia. Marine and Petroleum Geology, 114, 104168. DOI: https://doi.org/10.1016/j.marpetgeo.2019.104168
  » https://doi.org/10.1016/j.marpetgeo.2019.104168
• Nauta, J., Leurs, G., Nieuwenhuis, B.O., Mathijssen, D.R.A.H., Olff, H., Bouma, T.J., van der Wal, D., Hijner, N., Regalla, A., Pontes, S.L. & Govers, L.L. 2024. Bioturbation by benthic stingrays alters the biogeomorphology of tidal flats. Ecosystems, 27(4), 493-507. DOI: https://doi.org/10.1007/s10021-024-00901-4
  » https://doi.org/10.1007/s10021-024-00901-4
• Nel, R., McLachlan, A. & Winter, D.P.E. 2001. The effect of grain size on the burrowing of two Donax species. Journal of Experimental Marine Biology and Ecology , 265(2), 219-238. DOI: https://doi.org/10.1016/s0022-0981(01)00335-5
  » https://doi.org/10.1016/s0022-0981(01)00335-5
• Olabarria, C., Urgorri, V. & Troncoso, J.S. 1998. The influence of physicochemical parameters on the distribution of dominant bivalve species in the ensenada do Baño (Ria de Ferrol) in Northwest of Spain. Apex, 13(3), 81-93.
• Palomo, G. & Iribarne, O. 2000. Sediment bioturbation by polychaete feeding may promote sediment stability. Bulletin of Marine Science, 67(1), 249-257.
• Palomo, G., Martinetto, P. & Iribarne, O. 2004. Changes in the feeding behavior of the deposit-feeding polychaete Laeonereis acuta on soft sediments inhabited by burrowing crabs. Marine Biology, 145(4), 657-667. DOI: https://doi.org/10.1007/s00227-004-1352-4
  » https://doi.org/10.1007/s00227-004-1352-4
• Pang, M., Xu, R., Zhu, T., Wang, C. & Kaisam, J.P. 2021. Water quality improvement measures at the Yagang cross-section in the Pearl River Delta based on the calculation of excessive pollutant fluxes. Water Supply, 21(4), 1778-1792. DOI: https://doi.org/10.2166/ws.2020.345
  » https://doi.org/10.2166/ws.2020.345
• Passarelli, C., Olivier, F., Paterson, D.M. & Hubas, C. 2012. Impacts of biogenic structures on benthic assemblages: microbes, meiofauna, macrofauna and related ecosystem functions. Marine Ecology Progress Series , 465(6), 85-97. DOI: https://doi.org/10.3354/meps09915
  » https://doi.org/10.3354/meps09915
• Passarelli, C., Olivier, F., Paterson, D.M., Meziane, T. & Hubas, C. 2014. Organisms as cooperative ecosystem engineers in intertidal flats. Journal of Sea Research , 92, 92-101. DOI: https://doi.org/10.1016/j.seares.2013.07.010
  » https://doi.org/10.1016/j.seares.2013.07.010
• Patel, S.J. & Desai, B.G. 2009. Animal-sediment relationship of the crustaceans and polychaetes in the intertidal zone around Mandvi, Gulf of Kachchh, Western India. Journal of the Geological Society of India, 74(2), 233-259. DOI: https://doi.org/10.1007/s12594-009-0125-6
  » https://doi.org/10.1007/s12594-009-0125-6
• Pennafirme, S., Machado, A.S., Machado, A.C., Lopes, R.T., Lima, I.C.B. & Crapez, M.A.C. 2019. Monitoring bioturbation by a small marine polychaete using microcomputed tomography. Micron, 121, 77-83. DOI: https://doi.org/10.1016/j.micron.2019.03.004
  » https://doi.org/10.1016/j.micron.2019.03.004
• Petrash, D.A., Lalonde, S.V., Gingras, M.K. & Konhauser, K.O. 2011. A surrogate approach to studying the chemical reactivity of burrow mucous linings in marine sediments. Palaios , 26(9), 594-600. DOI: https://doi.org/10.2110/palo.2010.p10-140r
  » https://doi.org/10.2110/palo.2010.p10-140r
• Rodríguez-Tovar, F.J., Nagy, J. & Reolid, M. 2014. Palaeoenvironment of Eocene prodelta in Spitsbergen recorded by the trace fossil Phycosiphon incertum. Polar Research, 33(1), 23786. DOI: https://doi.org/10.3402/polar.v33.23786
  » https://doi.org/10.3402/polar.v33.23786
• Rowshan, O., Sakhaei, N., Zolgharnein, H., Paknezhad, H. & Taheri, M. 2023. Research article: spatial distribution and structure of benthic polychaete communities in shallow waters of the south Caspian Sea, Iran. Iranian Journal of Fisheries Sciences, 22(1), 44-65.
• Sendra, J., Reolid, M. & Reolid, J. 2019. Palaeoenvironmental interpretation of the Pliocene fan-delta system of the Vera Basin (SE Spain): fossil assemblages, ichnology and taphonomy. Palaeoworld, 29(4), 769-788. DOI: https://doi.org/10.1016/j.palwor.2019.11.001
  » https://doi.org/10.1016/j.palwor.2019.11.001
• Shetty, A. & Goyal, A. 2022. Total organic carbon analysis in water - a review of current methods. Materials Today Proceedings, 65(8), 3881-3886. DOI: https://doi.org/10.1016/j.matpr.2022.07.173
  » https://doi.org/10.1016/j.matpr.2022.07.173
• Song, W. & Li, Y. 2023. Tidal flat microbial communities between the Huaihe estuary and Yangtze River estuary. Environmental Research, 238(1), 117141. DOI: https://doi.org/10.1016/j.envres.2023.117141
  » https://doi.org/10.1016/j.envres.2023.117141
• Sun, T., Liu, C., Li, X., An, D., Yu, H., Ma, Z. & Liu, F. 2019. The effect of substrate grain size on burrowing ability and distribution characteristics of Perinereis aibuhitensis. Acta Oceanologica Sinica, 38(12), 52-58. DOI: https://doi.org/10.1007/s13131-019-1348-z
  » https://doi.org/10.1007/s13131-019-1348-z
• Tian, S., Tong, Y. & Hou, Y. 2019. The effect of bioturbation by polychaete Perinereis aibuhitensis on release and distribution of buried hydrocarbon pollutants in coastal muddy sediment. Marine Pollution Bulletin, 149, 110487. DOI: https://doi.org/10.1016/j.marpolbul.2019.110487
  » https://doi.org/10.1016/j.marpolbul.2019.110487
• Virtasalo, J.J., Leipe, T., Moros, M. & Kotilainen, A.T. 2011. Physicochemical and biological influences on sedimentary-fabric formation in a salinity and oxygen-restricted semi-enclosed sea: Gotland Deep, Baltic Sea. Sedimentology , 58(2), 352-375. DOI: https://doi.org/10.1111/j.1365-3091.2010.01166.x
  » https://doi.org/10.1111/j.1365-3091.2010.01166.x
• Wang, Y., Gou, S., Wang, C., Zhang, G., Uchman, A. & Wetzel, A. 2024. The crab Macrophthalmus japonicus burrows on a tidal flat of the Yellow River Delta in China: their 3D morphological variability in relation to physicochemical conditions and palaeoichnological perspective. Palaeogeography, Palaeoclimatology, Palaeoecology , 638, 112037. DOI: https://doi.org/10.1016/j.palaeo.2024.112037
  » https://doi.org/10.1016/j.palaeo.2024.112037
• Wang, Y., Wang, X., Uchman, A., Hu, B. & Song, H. 2019. Burrows of the polychaete Perinereis aibuhiutensis on a tidal flat of the yellow river delta in China: implications for the ichnofossils Polykladichnus and Archaeonassa. Palaios , 34(5), 271-279. DOI: https://doi.org/10.2110/palo.2018.105
  » https://doi.org/10.2110/palo.2018.105
• Wang, Y.-Y., Zhang, Y.-B., Gou, S.-L. & Zhang, G.-C. 2025. 3D morphology of crab (Macrophthalmus japonicus) burrows from the Pearl River Delta front, China: the physicochemical factors, with implications for the rock record. Journal of Palaeogeography, 14(1), 203-220. DOI: https://doi.org/10.1016/j.jop.2024.09.004
  » https://doi.org/10.1016/j.jop.2024.09.004
• Wei, Z., Huang, S., Xu, J., Yuan, C., Zhang, M. & Wang, C. 2024. Geochemical evolution of geothermal waters in the Pearl River Delta region, South China: insights from water chemistry and isotope geochemistry. Journal of Hydrology: Regional Studies, 51, 101670. DOI: https://doi.org/10.1016/j.ejrh.2024.101670
  » https://doi.org/10.1016/j.ejrh.2024.101670
• Xiao, M. & Cui, Y. 2021. Source of evaporation for the seasonal precipitation in the Pearl River Delta, China. Water Resources Research, 57(8), e2020WR028564. DOI: https://doi.org/10.1029/2020wr028564
  » https://doi.org/10.1029/2020wr028564
• Yang, F., Ji, X., Zhang, W., Zou, H., Jiang, W. & Xu, Y. 2022. Characteristics and driving mechanisms of salinity stratification during the wet season in the Pearl River Estuary, China. Journal of Marine Science and Engineering, 10(12), 1927. DOI: https://doi.org/10.3390/jmse10121927
  » https://doi.org/10.3390/jmse10121927
• Zhang, W., Cao, Y., Zhu, Y., Wu, Y., Ji, X., He, Y., Xu, Y. & Wang, W. 2017. Flood frequency analysis for alterations of extreme maximum water levels in the Pearl River Delta. Ocean Engineering, 129, 117-132. DOI: https://doi.org/10.1016/j.oceaneng.2016.11.013
  » https://doi.org/10.1016/j.oceaneng.2016.11.013
• Zhang, W., Ruan, X., Zheng, J., Zhu, Y. & Wu, H. 2010. Long-term change in tidal dynamics and its cause in the Pearl River Delta, China. Geomorphology, 120(3-4), 209-223. DOI: https://doi.org/10.1016/j.geomorph.2010.03.031
  » https://doi.org/10.1016/j.geomorph.2010.03.031

AI USE STATEMENT

During manuscript compilation, AI resources were only utilized to refine English diction and enhance overall manuscript legibility. All research conceptualization, original text composition, experimental design and statistical data analysis were accomplished independently by the author team; every figure and table was self-generated, with no artificial intelligence adopted for graph drafting or computational processing.

FUNDING

This research was supported by the National Natural Science Foundation of China (Grant No. 42172130) and the Youth Backbone Teacher Training Program of Henan Provincial Universities (Grant No. 2023GGJS055).

*

Corresponding author: [e-mail]

Associate Editor:

Maikon Di Domenico

CONFLICTS OF INTEREST

We declare that we have no financial or personal relationships with other individuals or organizations that could inappropriately influence our work. There are no professional or other personal interests of any nature.

Publication Dates

• Publication in this collection
  21 Sept 2026
• Date of issue
  2026

History

• Received
  04 Mar 2025
• Accepted
  20 May 2026