Spatiotemporal variations in fine-scale habitat use of the world’s second largest population of humpback dolphins

Abstract

We assessed habitat use by the population of Indo-Pacific humpback dolphin, Sousa chinensis, in the waters off Zhanjiang, China, by performing boat-based surveys between 2013 and 2018. In total, we gathered 253 sightings of humpback dolphins. To assess habitat use of humpback dolphins within the study area, we measured two spatial metrics at each sighting site: WD_T (tide-calibrated water-depth) and DS (distance to the nearest shore). Results showed that dolphins mainly were observed in shallow (WD_T: 8.46 ± 5.13 m, mean ± SD) and inshore (DS: 2.17 ± 2.14 km) waters. Their preference of inhabiting shallow waters was more apparent during the wet season (April–September) than during the dry season (October–March); however, they were encountered in waters much closer to shore during the dry season than the wet season. By weighting survey effort, our sighting density maps further confirmed that humpback dolphins changed their habitat use between wet and dry seasons. Such spatiotemporal variations in dolphin habitat use might be associated with spatiotemporal movements of their prey. Our findings provide insights into variations in fine-scale habitat use of inshore apex predators, and also assist to designate proper conservation measures for these vulnerable animals.

栖息于中国湛江近海水域的中华白海豚种群是世界第二大的驼海豚种群。针对这一重要种群，本研究于2013至2018年在湛江东部近海进行了海上调查，共获得253次中华白海豚目击。为探讨该水域的海豚栖息地利用规律，每次取样测量了目击位置的潮汐校准水深（WDT）和最近离岸距离（DS）。分析结果表明，湛江的中华白海豚主要出没于浅水（WDT: 8.46 ± 5.13 m, 平均值 ± 标准差）和近岸（DS: 2.17 ± 2.14 km）区域。相对于干季（10至3月），它们对浅水区的偏好比在湿季（4至9月）更加明显；然而跟湿季相比，它们在干季会更靠近岸边。通过加权考量，目击密度图进一步证明了它们确实会在不同季节改变栖息地利用特征。栖息地利用的季节性可能与中华白海豚食物资源的迁移变化有关。本研究为这些近岸顶级捕食者栖息地利用的季节规律和变化提供了考量，将有助于针对这些濒危动物制定相应保护措施。

近岸栖息地, 栖息地利用, 中华白海豚, 移动, 季节, 浅水区, 潮汐, 湛江

coastal habitats, habitat use, humpback dolphins, movements, season, shallow water, tide, Zhanjiang

One of the most important actions to be undertaken in conserving endangered species is protecting their populations in their natural habitats (Jefferson and Hung 2004; Liu et al. 2020), including habitat conservation and management. Effective habitat conservation and management require baseline information on habitat-use patterns of wild animal populations at a variety of spatial and temporal scales (Wilson et al. 2004), which is particularly challenging when monitoring highly mobile species such as cetaceans (Gilles et al. 2016). The habitat-use patterns of cetaceans commonly are believed to be a function of habitat heterogeneity and their own biological requirements, which are the result of adaptations to different environments (Bräger et al. 2003; Fury and Harrison 2011). Spatiotemporal variations in habitat use have been reported for many cetacean species, particularly those delphinids that occur in coastal waters where there is an urgent need for habitat conservation and management, including bottlenose dolphins (Tursiops spp.—Allen et al. 2001; Cribb et al. 2008), Hector’s dolphins (Cephalorhynchus hectori—Bräger et al. 2003; Rayment et al. 2010), and Guiana dolphins (Sotalia guianensis—Wedekin et al. 2010).

Indo-Pacific humpback dolphins (Sousa chinensis Osbeck, 1765), one of four species in the genus Sousa (humpback dolphins), inhabit shallow and near-shore waters of the Indo-Pacific region (Jefferson and Curry 2015; Li 2020). Their general preference for estuaries and coastal habitats has been documented widely in previous studies (Jefferson and Hung 2004; Jefferson and Smith 2016). Sousa chinensis was classified as “Near Threatened” (NT) in the IUCN Red List of Threatened Species in 2008, but was reassessed recently as “Vulnerable” (VU, A3cd+4cd) given the increasing anthropogenic threats to this species (Jefferson et al. 2017). In China, it has been listed as one of the Grade I National Key Protected Animals by the Chinese Wild Animal Protection Act of 1988 (Chen et al. 2009). Such designation provides this species with the same protection priority as the Yangtze River dolphin (Baiji, Lipotes vexillifer), which has been declared functionally extinct since 2006 (Turvey et al. 2007).

The temporal variations in habitat use of humpback dolphins, such as seasonal (Lin et al. 2015; Wang et al. 2016); tidal (Chen et al. 2007; Lin et al. 2013); diel (Pine et al. 2017); and lunar (Wang et al. 2015; Li et al. 2018), typically are habitat-specific and affected by fine-scale environmental parameters. The humpback dolphins in the Xiamen Bay, China, for instance, mainly foraged in shallow and inner harbors during the dry season, but occupied wide peripheral areas during the wet season (Chen et al. 2007; Wang et al. 2016). Conversely, humpback dolphins along the northern coast of Beibu Gulf manifested a dissimilar pattern: they generally were encountered in shallow and inshore waters near an estuary during the wet season, but moved toward relatively deep, off-estuary waters during the dry season (Li et al. 2018). In addition, humpback dolphins also have been found to occur in specific areas during particular tidal or diel phases, as described for the Eastern Taiwan Strait (Lin et al. 2013) and Pearl River Estuary (Wang et al. 2015; Pine et al. 2017).

The population of humpback dolphins in the coastal waters of eastern Zhanjiang, China, first was described in 2007 (Zhou et al. 2007). By using photo-identification techniques, a follow-up study resulted in an abundance estimate of 1,485 individuals (95% confidence interval [CI] = 1,371–1,629); that population size made it be the second largest population of humpback dolphins (genus Sousa) in the globe (Xu et al. 2012, 2015). Unfortunately, this population and its habitats are vulnerable to a variety of human activities, including fishing activities (Liu et al. 2020); inshore aquaculture (Xu et al. 2012); shipping traffic (Liu et al. 2017a; Dong et al., 2019); and water pollution (Xu et al. 2015). There is an urgent need for robust conservation and effective management actions. However, we still lack knowledge on habitat-use patterns of humpback dolphins in this region. In particular, spatiotemporal variations in habitat use of this population have not been well examined.

To address this knowledge gap, boat-based surveys were carried out from 2013 to 2018 in the eastern waters of Zhanjiang, China. To investigate the habitat use pattern of the world’s second largest population of humpback dolphins, we collected data on dolphin occurrence as well as habitat characteristics (water-depth and distance to the nearest shore). This study aims to provide a better understanding of how Zhanjiang humpback dolphins used their habitats at a variety of temporal scales, and help propose more effective initiatives for protecting this threatened population.

Materials and Methods

Study area.—

The study area (20°40′–21°20′N, 110°10′–110°40′E) is a semienclosed subtropical embayment along the eastern coast of Zhanjiang, China, located in the northern section of South China Sea (Fig. 1A). The study area is constituted by sandy/muddy seafloor with a maximum depth of ~40 m (Xu et al. 2015; Liu et al. 2017a), which primarily consists of two sections: Leizhou Bay, and the mouth area of Zhanjiang Port (Fig. 1B). The climate in the study area is defined as biseasonal, with a wet season from April to September, and a dry season from October to March (Wang et al. 2015, 2016; Liu et al. 2017b).

Fig. 1.

—(A) Map of the study area: the eastern waters of Zhanjiang, China; (B) two main areas to investigate habitat use of Indo-Pacific humpback dolphins (Sousa chinensis): the mouth area of Zhanjiang Port and Leizhou Bay.

Data collection.—

We carried out boat-based surveys in 2 months (October and November) of 2013 and quarterly from January 2015 to May 2018, using either a 12-m wooden fishing boat (60 horsepower [HP] outboard engine) or a 7-m fiberglass speedboat (75 HP outboard engine). During the surveys, we investigated shallow and inshore waters of depth less than 30 m and distant from shore less than 20 km, because such waters typically are preferred by humpback dolphins (Jefferson and Curry 2015). On the front of the boat, a minimum of two experienced observers visually searched for humpback dolphins with naked eyes and/or Fujinon 7 × 50 FMT-SX Polaris binoculars (Fujifilm Holdings Corporation, Tokyo, Japan—Li et al. 2016). The term “sighting” was defined as one or more humpback dolphins being encountered. For each sighting, we approached the dolphin(s) slowly (< 8 km/h) and kept a safe distance (10–50 m) behind or to the side of them (Wang et al. 2016). We recorded date, time, and location, using a portable GPS receiver (Garmin GPSMAP 78s; Garmin International Ltd., Olathe, Kansas), and also recorded the estimated number of animals (i.e., group size, min/best/max) on a standardized effort log. In addition, we measured the water-depth from the boat either by using a fish detector (Lowrance HDS7; Lowrance Electronics, Tulsa, Oklahoma) or a depth sounder (HONDEX PS-7; HONDEX–Honda Electronics, Ltd., Toyohashi, Aichi, Japan) at each sighting site and every 30 min during each survey. We only conducted the surveys under visual conditions without fog or rain and sea states of Beaufort Scale ≤ 3.

Data analysis.—

We used two spatial metrics: WD_T (tide-calibrated water-depth at each sighting site) and DS (distance from each sighting site to the nearest shore; Atkins et al. 2004; Li et al. 2018) to characterize habitat use of humpback dolphins in the study area. We converted on-board measured water-depth data (WD) to tidal-phase water-depth data (WD_T) according to the tidal height (H_T—Wu et al. 2017):

$${\displaystyle \begin{array}{l}{\displaystyle \mathrm{W}{\mathrm{D}}_{\mathrm{T}}=\mathrm{W}\mathrm{D}-(\frac{{\mathrm{H}}_{\mathrm{T}+1}-{\mathrm{H}}_{\mathrm{T}}}{60}\times \mathrm{M}+{\mathrm{H}}_{\mathrm{T}})+{\mathrm{H}}_{\mathrm{R}},}\end{array}}$$

where T and M are the hour and minute of recordings. Data on H_T at the Port of Zhanjiang (21°10′N, 110°24′E) were obtained from an open-access website, i.e., China Port Service (http://www.chinaports.com/chaoxi—Wang et al. 2015). In the study area, the reference plane of high tide (H_R) was set up at 220 cm below the datum sea level.

We measured DS values using a tool-module of proximity analysis in the ArcGIS 10.1 (ESRI, Redlands, California). The Pearson correlation test was carried out to examine whether WD_T and DS were dependent variables. The Shapiro–Wilk tests were conducted to examine the normality of WD_T and DS. Because both metrics failed to pass the test of normality, we transformed them into normal Gaussian distribution using a Box–Cox transformation. To examine the temporal variations in WD_T and DS, we included three temporal factors: survey year (2013, 2015, 2016, 2017, and 2018), season (wet and dry), and tide (high, ebb, low and flood; see Wang et al. 2015), as explanatory variables in a three-way analysis of variance (ANOVA). We examined the homogeneity of variance using Levene’s test. The null hypothesis was that there was no difference in the values of WD_T and DS across different years, seasons, and tidal phases, separately. In total, we included three main effects and four interactions into the ANOVA.

Once significant differences were found in either main factor, we performed a one-way ANOVA with the post hoc pairwise multiple comparison tests using Tukey’s HSD (equal variances, P > 0.05) or Tamhane’s T2 method (unequal variances, P < 0.05). Based on the ANOVA results, we pooled all the humpback dolphin sightings into two seasonal serials (i.e., wet and dry) to display seasonal variations in WD_T and DS. We used boxplots to illustrate differences in WD_T and DS between seasons. We also plotted the mean values of DS with error bars (standard deviations, SDs) by showing the four tidal phases (high, ebb, low, and flood) in two seasons (wet and dry). We classified the DS values into three categories: 0–2, > 2–4, and ≥ 4 km; we then plotted radar diagrams to show the percentage of DS values observed at each recorded tidal phase in different seasons (Mahmud et al. 2018). All statistical analyses were carried out in SPSS 16.0 (SPSS Inc., Chicago, Illinois), with a defined significance level of P < 0.05.

The study area was divided into 2 × 2 km grid cells using ArcGIS 10.1; the survey effort in each grid cell was calculated to show survey intensity by season. Because some grid cells were partly occupied by land, survey effort was standardized by weighting the accessible percentage of water area by humpback dolphins (Wu et al. 2017). To quantitatively show comparable sighting density, the number of sightings in each grid cell was divided by the total survey effort in the grid cell (Liu et al. 2020). In addition, individual density maps were created by showing the number of individuals recorded in each grid cell; this was also weighted by the total survey effort in each grid cell. To minimize the variance, only the best estimate of group size by observer-based counts was used for all groups. Because a minority of groups (24 out of 253) was not determined with available group sizes, their estimates were defined as the mean size of the 229 determined groups.

Results

During the five survey years, we undertook a total of 174 survey days, resulting in a total of 1,051 survey hours, covering a survey effort of 11,676 km (Table 1; Fig. 2A). We recorded 253 sightings of Indo-Pacific humpback dolphins within the study area (Table 1), with a mean group size of 9.4 ± 7.2 individuals (mean ± SD; range: 1–48). The number of humpback dolphin sightings during different seasons and tidal phases are summarized in Table 2. All 253 sightings are shown, distributed by year, season, and tidal phase, in Figs. 2B–D, respectively. For more than 70% of sightings, WD_T values were less than 10 m, with the majority (85%) less than 15 m (Fig. 3A). In addition, 68% of DS values were smaller than 4 km, with the majority (96%) less than 8 km (Fig. 3B). On average, humpback dolphins were sighted in shallow waters, at depths of 8.46 ± 5.13 m (1.4–28.4 m) and inshore waters 2.17 ± 2.14 km (0.05–10.91 km) distant from the nearest shore (Fig. 3C). No significant linear correlation was observed between the WD_T and DS (Pearson correlation coefficient, r = −0.061, P = 0.342; Fig. 3C).

Table 1.

Summary of annual survey details of Indo-Pacific humpback dolphins (Sousa chinensis) in the eastern waters of Zhanjiang, China, from 2013 to 2018.

Year	No. of survey days	Survey effort (km)	Survey hours (h)	No. of sightings
2013	4	220	25	4
2015	55	3,638	422	91
2016	59	3,692	317	66
2017	46	3,546	215	78
2018	10	580	72	14
Total	174	11,676	1,051	253

Table 2.

Number of sightings of Indo-Pacific humpback dolphins (Sousa chinensis) during different seasons and tidal phases in the eastern waters of Zhanjiang, China, from 2013 to 2018.

Year	Season (period)	Tidal phase	No. of sightings
2013	Dry (November–December)	High	1
		Ebb	1
		Low	0
		Flood	2
2015	Dry (January, October–November)	High	9
		Ebb	11
		Low	4
		Flood	6
	Wet (April–May, July–August)	High	16
		Ebb	8
		Low	13
		Flood	24
2016	Dry (March, October–November)	High	11
		Ebb	4
		Low	3
		Flood	11
	Wet (June–July)	High	3
		Ebb	6
		Low	7
		Flood	21
2017	Dry (March, November)	High	5
		Ebb	1
		Low	1
		Flood	3
	Wet (April–September)	High	10
		Ebb	17
		Low	17
		Flood	24
2018	Wet (April–May)	High	1
		Ebb	2
		Low	3
		Flood	8

Fig. 2.

—(A) Survey routes throughout the study period (October–November 2013 and from January 2015 to May 2018). Sighting locations of humpback dolphins in the study area according to the categories of (B) survey year (2013, 2015, 2016, 2017, and 2018), (C) season (wet and dry), and (D) tidal phase (high, ebb, low, and flood).

Fig. 3.

—Histograms of (A) WD_T (tide-calibrated water-depth) and (B) DS (distance to the nearest shore) at each sighting site of Indo-Pacific humpback dolphins (Sousa chinensis); (C) scatterplots and mean values of WD_T versus DS.

ANOVA results indicated that the WD_T values were associated with season (F = 6.372, P = 0.038), but not with year (F = 0.183, P = 0.670), tide (F = 1.372, P = 0.252), or other interactions (year × season, F = 0.276, P = 0.600; year × tide, F = 2.386, P = 0.070; season × tide, F = 1.087, P = 0.356; year × season × tide, F = 1.941, P = 0.165; Table 3). The DS values were associated with season (F = 1.073, P = 0.040), tide (F = 2.413, P = 0.048), and season × tide (F = 1.495, P = 0.041), but not with year (F = 0.119, P = 0.730; Table 3). The WD_T values were significantly larger during the dry season (8.93 ± 0.49 m) than that the wet season (7.24 ± 0.42 m; Tamhane’s T2 test, F = 3.932, P = 0.048; Fig. 3A). In addition, humpback dolphins moved significantly closer to the shore during the dry season (2.24 ± 0.28 km) than during the wet season (3.67 ± 0.20 km; Tamhane’s T2 test, F = 0.610, P = 0.035; Fig. 3B). Humpback dolphins mainly used shallow waters, particularly more so during the wet season than the dry season (Figs. 4C and 4E). Furthermore, a seasonal shift in near-shore tendency also was shown in the histograms of DS (Figs. 4D and 4F).

Table 3.

Results of three-way analysis of variance (ANOVA) testing the difference in habitat use of Indo-Pacific humpback dolphins (Sousa chinensis) across years, seasons, and tidal phases, separately. Two metrics were included at each sighting site to indicate dolphin habitat use: WD_T (tide-calibrated water-depth) and DS (distance to the nearest shore). *Asterisks denote statistical significance (P < 0.05).

Metrics	Source of variation	Type III sum of squares	d.f.	Mean square	F	P
WDT	Corrected model	42.780	23	1.156	1.206	0.008*
	Intercept	0.017	1	0.017	0.018	0.894
	Year	0.175	3	0.175	0.183	0.670
	Season	6.111	1	6.111	6.372	0.012*
	Tide	3.948	3	1.316	1.372	0.252
	Year × Season	0.265	3	0.265	0.276	0.600
	Year × Tide	6.865	9	2.288	2.386	0.070
	Season × Tide	3.127	3	1.042	1.087	0.356
	Year × Season × Tide	1.862	3	1.862	1.941	0.165
DS	Corrected model	45.095	23	1.219	1.313	0.021*
	Intercept	0.010	1	0.010	0.010	0.919
	Year	0.111	3	0.111	0.119	0.730
	Season	0.996	1	0.996	1.073	0.040*
	Tide	6.716	3	2.239	2.413	0.048*
	Year × Season	0.846	3	0.846	0.912	0.341
	Year × Tide	7.774	9	2.591	2.792	0.364
	Season × Tide	4.161	3	1.387	1.495	0.041*
	Year × Season × Tide	0.711	3	0.711	0.766	0.382

Fig. 4.

—Median (black horizontal line) and mean (open circle) values of (A) WD_T (tide-calibrated water-depth) and (B) DS (distance to the nearest shore) at each sighting site of Indo-Pacific humpback dolphins (Sousa chinensis). Histograms of WD_T and DS values during the (C and D) wet season and (E and F) dry season. The shaded boxes represent the range of the first quartile to the third quartile, and the error bars represent the range of all data. Normal distribution curve was fitted in each histogram.

During the wet season, the humpback dolphins used inshore waters significantly closer to the nearest shore at the high-tide phase (DS: 2.27 ± 0.41 km) or the low-tide phase (DS: 2.24 ± 0.56 km) than those at the ebb-tide phase (DS: 3.24 ± 0.66 km) or flood-tide phase (DS: 3.41 ± 0.57 km; Tukey’s HSD test: P_{high versus low} = 0.317, P_{high versus ebb} = 0.039, P_{high versus flood} = 0.026, P_{low versus ebb} = 0.044, P_{low versus flood} = 0.019, P_{ebb versus flood} = 0.516) (Fig. 5A). During the dry season, humpback dolphins preferred to use waters significantly further from the nearest shore at the flood-tide phase (DS: 3.53 ± 0.32 km) rather than at high-tide (DS: 2.88 ± 0.44 km) and ebb-tide (DS: 2.86 ± 0.55 km), while they preferred to use waters significantly closer to the nearest shore at low-tide (DS: 1.86 ± 0.40 km) rather than at other tidal phases (Tukey’s HSD tests: P_{flood versus high} = 0.045, P_{flood versus ebb} = 0.033, P_{flood versus low} = 0.021, P_{high versus ebb} = 0.028, P_{low versus high} = 0.012, P_{low versus ebb} = 0.003; Fig. 5A). Approximately half of the DS values between 0 and 2 km during the wet season occurred at low and high tide (Fig. 5B). Almost 80% of DS values between 0 and 2 km during the dry season occurred during low tide (Fig. 5C).

Fig. 5.

—(A) Mean values of DS (distance to the nearest shore) at each sighting site of Indo-Pacific humpback dolphins (Sousa chinensis), categorized into four tidal phases (high, ebb, low, and flood) during the wet and dry season. Error bars show the standard deviation. Asterisks represent statistical significance (P < 0.05). Radar diagrams show percentage of DS values observed at each recorded tidal phases (high, ebb, low, and flood) during the (B) wet season and (C) dry season.

During the wet and dry seasons, 7,417 and 4,259 km were surveyed, respectively (Figs. 6A and 7A). Of the 253 sightings, 176 (69.6%) occurred in the wet season, and 77 (30.4%) in the dry season (Figs. 6B and 7B). There was more survey effort and the survey area was larger during the wet season (Fig. 6B) than during the dry season (Fig. 7B). However, the sighting encounter rate (number of sightings per 100 km) in the wet season (2.37) was similar to the encounter rate in the wet season (1.81). Although group sizes in the wet season (8.9 ± 7.4) were similar to those in the dry season (10.1 ± 7.9; P = 0.125), the individual encounter rate (number of dolphins per 100 km) in the wet season (21.9) was larger than in the wet season (18.3; P = 0.022). Overall, both sighting density and individual density maps showed humpback dolphins occupied a greater area during the wet season than the dry season (Figs. 6C, 6D, 7C, and 7D).

Fig. 6.

—Wet season data serials: (A) survey routes and sighting locations of Indo-Pacific humpback dolphins (Sousa chinensis) in the study area, (B) survey intensity, i.e., accumulated survey distances within each grid cell (unit: 100 km), (C) sighting density, i.e., number of humpback dolphin sightings per 100 km in each grid cell weighted by survey intensity, and (D) individual density, i.e., number of humpback dolphins recorded in each grid cell per 100 km.

Fig. 7.

—Dry season data serials: (A) survey routes and sighting locations of Indo-Pacific humpback dolphins (Sousa chinensis) in the study area, (B) survey intensity, i.e., accumulated survey distances within each grid cell (unit: 100 km), (C) sighting density, i.e., number of humpback dolphin sightings per 100 km in each grid cell weighted by survey intensity, and (D) individual density, i.e., number of humpback dolphins recorded in each grid cell per 100 km during the wet season.

Discussion

Our data showed that humpback dolphins along the eastern coast of Zhanjiang, China, tended to use shallow, inshore waters. This finding is consistent with studies of humpback dolphins in other regions, including: Hong Kong (Jefferson and Smith 2016); South Africa (Karczmarski et al. 2000; Atkins et al. 2004); Xiamen (Chen et al. 2007; Wang et al. 2016); southwest Hainan (Li et al. 2016); Beibu Gulf (Wu et al. 2017; Li et al. 2018); and Taiwan (Dares et al. 2014). All these studies indicated that humpback dolphins are obligate shallow-water delphinids that have a strong preference for estuarine and near-shore habitats (Jefferson and Hung 2004; Jefferson and Curry 2015).

We detected no correlation between WD_T and DS values, which were measured at the sighting sites of Zhanjiang humpback dolphins. These two spatial metrics therefore could be robust indicators to represent habitat-use pattern of humpback dolphins within the confines of the study area (Atkins et al. 2004; Li et al. 2018). We examined a variety of temporal factors hypothesized to have complex influences on habitat use of Zhanjiang humpback dolphins. Seasonal influences on humpback dolphin habitat use have been observed in other regions, including the Pearl River Estuary (Jefferson 2000; Chen et al. 2010; Wang et al. 2015); Sanniang Bay (Li et al. 2018); Xiamen Bay (Chen et al. 2007; Wang et al. 2016); and Xin Huwei River Estuary (Lin et al. 2013, 2015). The seasonal pattern observed in the study area was similar to that observed in Sanniang Bay (Li et al. 2018): the humpback dolphins in these two regions were sighted primarily in shallower waters during the wet season, and in relatively deeper waters during the dry season. However, humpback dolphins in our study area inhabit waters relatively closer to the shore during the dry season, which is different from those observed in the Sanniang Bay, where dolphins occurred in estuarine waters relatively further from the shore during the dry season (Li et al. 2018). Furthermore, our seasonal pattern also is dissimilar to that documented in Xiamen Bay (Chen et al. 2007; Wang et al. 2016), where humpback dolphins usually inhabit inner and shallow-water harbors during the dry season, but move seaward during the wet season. Overall, our data and the previously published evidence indicate that seasonal changes in humpback dolphin habitat use vary from habitat to habitat.

Our data also revealed a complex tidal influence on the habitat use of humpback dolphins from Zhanjiang across different seasons. This area comprises extensive near-shore waters, as the majority of waters are shallower than 40 m with the semidiurnal tide (Xu et al. 2012, 2015; Liu et al. 2017a). In such a semienclosed environment, tidal activities could greatly influence a variety of oceanographic features, which may further alter the prey availability of humpback dolphins at spatial and temporal scales (Hastie et al. 2004; Kimura et al. 2012; Taylor et al. 2016). Fish schools in the coastal/estuarine waters were observed to migrate regularly with the tide between subtidal resting grounds and intertidal feeding grounds (Gibson 2003; Barros et al. 2004; Paitach et al. 2017). Prey species of humpback dolphins such as lion-head fishes (Collichthys spp.; Perciformes: Sciaenidae), sardines (Sardinella spp.; Clupeiformes: Clupeidae), and anchovies (Thryssa spp.; Clupeiformes: Engraulidae) have been found to enter the intertidal zone during high tide (Lin et al. 2013; Li et al. 2018); and this might be a factor driving tidal influence on habitat use of Zhanjiang humpback dolphins.

While eastern Zhanjiang is a semienclosed area with extensive shallow waters providing a large area for humpback dolphins, these did not use the accessible habitats with equal probabilities across different seasons. Although we applied a greater survey effort across a larger area during the wet season, effort-corrected sightings occurred across a greater area during the wet season. Such spatiotemporal variations in habitat use likely were synchronized temporally with the movements of their prey (Wilson et al. 1997; Wedekin et al. 2007, 2010; Taylor et al. 2016). This point was supported from previous studies in the Xin Huwei River Estuary, where the occurrence of humpback dolphins was associated seasonally with snapping shrimp sounds (Lin et al. 2013, 2015). In addition, spatiotemporal variability in habitat-use pattern of Zhanjiang humpback dolphins might affect vulnerability of the population to human-caused stressors, such as toxic pollutants from runoffs, and entanglements or added stranding risk due to fishing activities across different seasons.

This study described the habitat-use patterns of the world’s second largest population of humpback dolphins, and showed their similarity or dissimilarity with respect to other humpback dolphin populations. Our results suggested that spatiotemporal variations in habitat use of humpback dolphins in Zhanjiang may be associated with prey availability across different seasons or tidal phases in fine-scale areas. In addition, we emphasized the importance of protecting the critical natural habitats of Zhanjiang humpback dolphins from increasing anthropogenic impacts in this region, including overfishing, intensive shipping activities, aquaculture, naval exercises, and coastal construction (Xu et al. 2015; Liu et al. 2020). Dolphin habitat use within the study area was not predicted by survey year; long-term monitoring plans are needed to detect habitat displacement and loss of humpback dolphins resulting from anthropogenic pressures in this region (Hartel et al. 2015; Wang et al. 2017). The findings of our study should be taken into consideration in conservation management measures for this threatened dolphin population (Wilson et al. 2004; Wang et al. 2016), for example, in establishing a network of marine protected areas based on spatiotemporal variations in dolphin habitat use.

Admittedly, more detailed studies are essential to explore the dynamic relationship between humpback dolphins and their habitats, particularly from the perspective of fisheries resources (Hastie et al. 2004) and human activities (Wang et al. 2017). We also acknowledge that occurrence data on humpback dolphins in this study only were gathered visually during the daytime. Other techniques such as passive acoustic monitoring and satellite tagging are recommended to provide additional baseline information on dolphin habitat use in this region, particularly during the night time (Lin 2015; Wang et al. 2015; Dong et al. 2017, 2019).

Acknowledgments

We are grateful to all colleagues and students in the Marine Mammal and Marine Bioacoustics Laboratory for their logistical support in the field work. Special thanks to Xiao Xu, Mingzhong Liu, Kuan Li, Jiancheng Dong, Xiaoming Tang, Wanxue Xu, and Francesco Caruso, for their participation in the survey. This research was financially supported by the National Natural Science Foundation of China (nos. 41422604, 41306169, and 41406182), Biodiversity Investigation, Observation and Assessment Program (2019–2023) of the Ministry of Ecology and Environment of China, the Indian Ocean Ninety-east Ridge Ecosystem and Marine Environment Monitoring and Protection, supported by the China Ocean Mineral Resources R & D Association (no. DY135-E2-4), and the Ocean Park Conservation Foundation of Hong Kong (nos. MM03-1415 and MM02-1516). The writing of this paper was supported in part by the China–UK Newton Fund Ph.D. Placement from the China Scholarship Council and British Council.