The life (history), diet and death of the blackspot shark (Carcharhinus sealei) from South-east Asia

Sourcing animals and collecting biological data

In total, 103 sharks matching the description of the cryptic look-alike species the blackspot shark (C. sealei) and Indonesian whaler shark (C. tjutjot) (White 2012) were sourced from a private seafood supplier as well as fish markets in Singapore. Specifically, 92 sharks were sourced from a private seafood supplier between November 2020 and December 2021. No sharks were sourced in February, March, May, July and August as the supplier did not have specimens in these months. Six sharks were sourced from Senoko Fishery Port in Singapore in 2019, and five sharks were sourced from Senoko Fishery Port in 2021. Animal ethics approval was not necessary because animals were not killed for this research but were sourced following mortality from commercial fishing gear. The import or catch location and fishing gear used were obtained where possible, and specimens were photographed, weighed, and stretched total length (STL, measured with dorsal portion of tail bent straight or stretched so upper lobe lies along body midline), fork length (FL) and pre-caudal length (PL), as described in Francis (2006), were taken to the nearest millimetre. Specimens were dissected in the laboratory and maturity for males and females was determined through observation of gonads and assigning them into discrete development stages (Table 1) following Walker (2005). The stomach and a section of thoracic vertebrae from underneath the dorsal fin was removed to enable diet and growth analyses. A small (<5-mm) fin clip was taken from the anal fin and stored in 70% ethanol before being transferred to 90% ethanol after 7 days. The cetyltrimethylammonium bromide (CTAB) DNA extraction protocol as described in Ward et al. (2005), was performed to help confirm the identity of the cryptic species (the blackspot shark or Indonesian whaler shark). DNA barcoding of the COI gene was performed using universal primers Fish F1 and R1 (Ward et al. 2005). Results were Sanger sequenced, trimmed in Genious Prime and blasted against the GenBank COI database. Matches to accession numbers with a grade of over 97% were accepted. In instances where DNA could not yield a result, morphological descriptions from White (2012) were used to discern the species, and age–growth analysis (detailed in next section) was conducted with and without these particular animals to ensure that their inclusion did not significantly affect results.

Diet analysis

Stomachs were excised and contents were separated by taxon and, if necessary, washed by submerging them in a beaker of tap water. Smaller items were examined under a dissecting microscope. Prey was identified to one of four taxonomic categories (species, genus, family or order). The numbers of whole animals and fragments were recorded for each taxonomic group. Digested tissue and fragments that could not be identified to a particular prey type were considered unidentifiable. Various subsamples were taken from 11 unidentifiable different prey items for DNA analysis by using the CTAB DNA extraction protocol (Ward et al. 2005).

Percentage frequency of occurrence (%FO), which is the proportion of individual stomachs containing a prey type, were calculated. Contents that were suspected to be bait (e.g. straight-edged, attached to hooks) were excluded from %FO analysis (Jabado et al. 2015). Whereas some studies exclude indigestible parts from such analysis (such as shells, otoliths and cephalopod beaks) (Potier et al. 2007; Bornatowski et al. 2014; Dicken et al. 2017) because they are not considered nutritionally valuable, this study included them, because in many instances they were the only identifiable parts of a prey item (Buckland et al. 2017). The number of individuals from a particular prey group (%N) could be calculated only for a subset of sharks (54.3%) because of the highly digested state of many prey (e.g. large number of fragments) and inability to separate content clumped together by mucus (Buckland et al. 2017); hence, %N was excluded from this study.

The Bray–Curtis coefficient was calculated (20 stress runs) and ADONIS (significance P < 0.05) was performed using the vegan package (ver. 2.6-4, J. Oksanen et al., see https://CRAN.R-project.org/package=vegan) in R (ver. 2022.12.0, R Foundation for Statistical Computing, Vienna, Austria, see https://www.r-project.org/) to assess similarity and differences in maturity, sex, season and breeding state. Non-metric multidimensional scaling analysis (NMDS) was performed with the ‘metaMDS’ function in the vegan package to visualise variation in diet by using %FO. Similarity percentages (SIMPER) were then performed using PRIMER (ver. 6, see https://www.primer-e.com/our-software/; Clarke and Gorley 2006) to confirm where these differences occurred.

Vertebral processing and age and growth analysis

Sections of thoracic vertebrae were removed from individual sharks (n = 103) and processed using methods described by Goldman (2005). All remaining tissue was removed from the vertebrae with a scalpel; the vertebrae were then sectioned and the five largest centra were selected and then soaked in 5% sodium hypochlorite solution for up to 3 min to remove residual tissue. Centra were then rinsed thoroughly with tap water and dried in an oven at 45–60°C. Two random centra per animal were selected and the posterior side of the centra (with the haemal arch opening) were attached to a glass microscope slide with Crystalbond 509 adhesive glue and a heat pad set at 250°C. The centra were sanded down against fine grain (400Cw) waterproof sandpaper set in tap water, until the middle of the centra was reached. The centra were then turned over and re-set in the microscope slide. The opposite side of the centra were sanded down until only the middle section of the centra remained at ~600 μm. These sections were then examined using a dissecting microscope; translucent and opaque bands (band pairs) were counted from the birthmark (Fig. 1), which is identified by a change in the angle of the corpus calcareum (Age 0) (Cailliet 2015). Each centra was photographed through a dissecting microscope (Olympus SZX7 body with a DP22 Olympus camera). To improve clarity of the band pairs, images of centra were digitally uploaded into Microsoft PowerPoint and Picture Editor was used to adjust contrast, colouration, and to apply filters to maximise clarity of band pairs, as was performed in Fisher and Hunter (2018). Two independent readers then assessed the images and estimated ages for each individual by counting band pairs. Discrepancies between the counts of the first and second reader were re-analysed until a consensus was reached. The interpretability of each vertebrae was scored according to the following definitions by McAuley et al. (2007): 0, unreadable; 1, bands visible but difficult to interpret; 2, bands visible but most bands difficult to interpret; 3, bands visible but a minority difficult to interpret; and 4, all bands unambiguous. Average percentage error (APE) was calculated to assess average initial disagreement between readers with the R package FSA (ver. 0.9.5, D. H. Ogle, J. C. Doll, A. P. Wheeler and A. Dinno, see https://fishr-core-team.github.io/FSA). Bayesian growth models are reported to outperform or match frequentist growth models (Smart and Grammer 2021). Bayesian growth models including von Bertalanffy (1938), Gompertz (Ratowsky 1990) and logistic, using Markov-chain Monte Carlo (MCMC) (Smart and Grammer 2021) were used to generate age–growth curves in R with the R package BayesGrowth (ver. 1.0.0, see https://cran.r-project.org/package=BayesGrowth), with best models selected based on leave-one-out-information-criterion (LOOIC) values (Smart and Grammer 2021). Generalised linear models (GLMs) with a binomial error structure and logit-link function were produced to determine the age-at-maturity at 50 and 95% lengths (L₅₀ and L₉₅) in the R package MASS (ver. 7.3–60, see https://CRAN.R-project.org/package=MASS; Venables and Ripley 2002). Age validation using live animals was not conducted.

Fig. 1.

Vertebral section from an 8-year-old male blackspot shark (Carcharhinus sealei) measuring 776-mm stretched total length (STL), caught from a handline fishery in Indonesia. The birthmark and band pairs are identified.

Hepatosomatic index (HSI)

The hepatosomatic index (HSI) is the ratio of liver weight to body weight, and is used as an indicator of energy reserves (Goede and Barton 1990). The HSI is calculated as:

where WL is liver weight and W is bodyweight. A three-way ANOVA was run using R to test for differences in HSI values among sex, season and maturity. Low-energy reserves are typically found after events of high metabolic activity such as migrations or reproduction (Reis and Figueira 2020).

Interview about the fishery

To learn more about the sharks and their fisheries, the private seafood supplier of sharks from Indonesia (n = 92) was interviewed through a semi-structured interview consisting of 22 questions (see the ‘Questionnaire’ section in the Supplementary material). This supplier not only traded sharks and rays but other seafood in general. The interview was conducted in English, following human ethics guidelines, and no remuneration was given. Questions covered (1) the fishery the sharks were sourced from, (2) the species itself and population trends observed, (3) the supply chain, (4) markets and use, and (5) solutions for their management. Some questions provided a range of answers for consideration, including the latter part of the interview (‘solutions for their management’); however, responses did not have to be restricted to options provided and the supplier was encouraged to elaborate where necessary.

Ethics statement

This research was undertaken with informed consent of those being interviewed under human ethics application H8683. Animal ethics approval was not necessary (as confirmed by the Institutional Animal Care and Use Committee (IACUC) at James Cook University, Singapore), because animals were not killed for this research, but were sourced following mortality from commercial fishing gear.

Species composition

Results from the DNA analysis confirmed 98 sharks as the blackspot shark (C. Sealei), and 5 sharks yielded no result. As these five sharks originated from the same catch location as the others, and more closely resembled morphological descriptions for the blackspot shark than the Indonesian whaler shark as described by White (2012), they were considered blackspot sharks for further analysis. In total, 101 blackspot sharks were caught in Indonesia, but near the Singapore Straits (male = 62, female = 39, immature = 60, mature = 41, gravid = 9), and only 2 were caught in Singapore waters (2 immature females). The size–frequency distribution (Fig. 2) shows that larger animals dominated the sample. The sex ratio of the total sample of sharks (n = 103: male = 62, female = 41) significantly differed from 1:1 (χ² = 4.282, d.f. = 1, P = 0.0385), and was particularly pronounced in the sharks caught from the handline fishery in Indonesia (n = 92: male = 58, female = 34; χ² = 6.261, d.f. = 1, P = 0.0123).

Fig. 2.

Size–frequency distribution of male (n = 62) and female (n = 41) blackspot sharks (Carchahrinus sealei) caught from fisheries in Indonesia (n = 101) and Singapore (n = 2) between 2019 and 2021. The sample was dominated by larger individuals (>600 mm STL), with a minimum size of 359 mm STL (from a female), a maximum size of 849 mm STL (from a female), and mean size of 678 mm STL. The red lines indicate the smallest sizes of maturity observed in the sample (709 mm STL for a male, and 730 mm STL for a female).

Diet

Of the total sample size of blackspot sharks, 8.7% (n = 9) had empty stomachs. This left a total sample size of 94 for further analysis (Table 2). Diet analysis showed that crustaceans, fish and cephalopods were the dominant prey items.

ADONIS and SIMPER analyses of the %FO showed dissimilarities between males and females (P = 0.028, 54.76 average dissimilarity). The main driver of this difference was the higher %FO of bony fishes in males, whereas females had higher %FO of cephalopods (for mature females only) and crustaceans (for immature females only). Another dissimilarity occurred between the age groups (P = 0.014, 54.17 average dissimilarity), with immature sharks of both sexes having a higher %FO of crustaceans (and only immature sharks had sand in their stomachs, reflecting bottom-feeding behaviour), and mature sharks having a higher %FO of cephalopods and bony fishes, with an exception among males, where immature sharks ate more cephalopods than did mature sharks.

Differences were also observed between immature males and immature females (P = 0.025, average dissimilarity 54.91). The main driver is that immature males have a higher %FO of bony fishes, whereas immature females have a higher %FO of crustaceans. Another difference was observed between mature males and mature females (P = 0.025, average dissimilarity 54.38). This is mainly due to mature males having a higher %FO of bony fishes, and mature females having a higher %FO of cephalopods (Fig. 3). No differences were detected between pregnant and non-pregnant specimens.

Fig. 3.

%FO of stomach contents for blackspot sharks (Carcharhinus sealei) from Singapore (n = 2) and Indonesia (n = 82) with identifiable prey in their stomach (n = 84): immature female (n = 20), mature female (n = 12), immature male (n = 32), mature male (n = 20).

Age–growth analysis

The smallest mature male was 709 mm STL (with 57 mm clasper length; Fig. 4), and the largest immature male was 786 mm STL (with 67-mm partially calcified claspers; Fig. 4). The smallest mature female was 730 mm STL and the largest immature female was 706 mm STL. Males and females showed a similar length–weight relationship, although females in the sample size attained larger sizes and heavier weights (Fig. 5).

Fig. 4.

Relation between size (stretched total length, STL), clasper length (mm) and maturity (black triangeles, uncalcified claspers; grey triangles, calcified claspers) for male (n = 64) blackspot sharks (Carcharhinus sealei), showing that maturity is attained from 709 mm STL and 57-mm clasper length.

Fig. 5.

Length–weight relationship for female (black circles, n = 41) and male (grey triangles, n = 62) blackspot sharks (Carcharhinus sealei).

Age bands could be read for all 103 samples; the majority of vertebrae, >75%, scored 2 or 3 of 5 for readability. The average percentage error (APE) was 14.66%, which is higher than the average reported APE in ageing studies (Campana 2001). The oldest agreed age (between the readers) from the study for this species was 11 years old for two females that were 757 and 825 mm STL. The oldest males in the sample were 9 years old at 789 and 801 mm STL (Fig. 6). MCMC analysis (Table 3) showed that of several potential growth models, the logistics model was the best-performing model when analysing males and females together (k-value of 0.37 year⁻¹); the Von Bertalanffy model was best when analysing females alone (k-value of 0.25 year⁻¹); and the Gompertz model was best when analysing males alone (k-value of 0.47 year⁻¹). Male and female blackspot sharks matured at similar ages, with 50% of males reaching maturity at 6.15 years and 95% by 8.92 years old, and 50% of females reaching maturity at 6.12 years and 95% by 8.64 years (Fig. 7).

Fig. 6.

Age–growth curve for 103 male and female blackspot sharks (Carcharhinus sealei) by using vertebral band counts and the MCMC analysis performed using Bayesian and frequentist models. Circles represent individual blackspot sharks. Lines indicate the modelled length and age values (green, frequentist; blue, Bayesian), with light blue shading indicating the 95% confidence intervals.

Fig. 7.

Logistic generalised linear models (GLMs) of estimated ages of (a) male and (b) female blackspot shark (Carcharhinus sealei) showing predictions of maturity at a given age. The model predicts a 50% age-at-maturity of 6.15 years, and a 95% age-at-maturity of 8.92 years for males, and a 50% age-at-maturity of 6.12 years, and a 95% age-at-maturity of 8.64 years for females.

Reproductive analysis

Of the 16 mature female blackspot sharks, 9 were gravid. Two were early-stage pregnancies, with two large yolky eggs inside the uterus but no embryos attached. The remaining seven gravid females had litters of two pups each; however, in one individual it appeared that one of the two pups had failed to develop properly. The largest embryos observed (341 and 333 mm STL from the same mother, Fig. 8b) were fully developed, and the smallest shark provided from the fishery measured 359 mm STL, suggesting that length at birth falls between 341 and 359 mm STL. The largest embryo (341 mm STL) was 43% of the size of the mother (785 mm STL). Of the nine gravid females, six had embryos that could be sexed, of which five were males and five were females (total embryos = 10), meaning that the sex ratio did not significantly differ from 1:1 (χ² = 0, d.f. = 1, P = 1.00). The youngest gravid female was 5 years old, and the oldest was 10 years old. Females showed various stages of pregnancy during the course of the year (Fig. 8b). Non-gravid mature females showed various ova diameters throughout the year (Fig. 8a), suggesting that reproduction is asynchronous and year-round. However, noticeably smaller ova were observed during December, suggesting a potential ‘pause’ during this month.

Fig. 8.

Reproductive data for female blackspot sharks (Carcharhinus sealei). (a) Largest ovarian egg diameter by month for all mature females (n = 16), showing both gravid (grey circles) and non-gravid (black circles) individuals, and (b) embryo (grey circles) and implanted egg (black circles) length by month for nine gravid individuals (where females carried two embryos, only the largest were selected for visualisation). Of gravid females (n = 9), only eight are visualised because the ova in one gravid female was damaged and not measurable.

Hepatosomatic index (HSI)

Results of the three-way ANOVA showed a statistically significant effect of sex on HSI; females overall had significantly higher HSI than did males (P = 0.0212–0.0261). The effect of month, maturity or in the interaction of sex and month, or of sex and maturity, was not significant (Supplementary Table S1, Fig. 9). The highest HSI value (5.9375) was observed in a mature female with an early-stage pregnancy (presence of two large yolky eggs in uterus). The second-highest HSI value (5.2910) was observed in an immature female in November. The lowest HSI values (<2.00) were observed in a mature female (caught in June), a mature male (caught in April) and an immature male (caught in December).

Fig. 9.

Hepatosomatic index (HSI) for male (n = 41) and female (n = 30) blackspot shark (Carcharhinus sealei) for which liver weight was recorded, between sexes and across months. Dark bars within each box represent the median value, the upper and lower boundaries of each box represent the interquartile range, the whiskers represent the total range, and the points outside the box represent outliers.

Interview: the fishery and supply chain

The private seafood supplier of 92 of the sharks sourced from Indonesia provided their general catch location (Fig. 10). He reported that animals were caught by small ‘sampan’ fishing boats that generally stay out for no longer than 12 h and use handlines. Fish (including snappers, Lutjanidae, groupers, Serranidae, catfish, Ariidae, jacks and trevallies, Carangidae) are the target species, with blackspot sharks being caught incidentally, but retained. Because the handlines are immediately retrieved once something is hooked, the sharks tend to still be alive when hauled in. Squid is reportedly used as bait in these handline fisheries, which was also confirmed by the presence of a sectioned (e.g. straight-edged) piece of squid inside one of the shark stomachs. Generally, every species caught by these boats has commercial value, and if the fishermen can sell it, they will land it ashore, unless it is not worth the ice and storage, which is reportedly rare. Within the region (Fig. 10), blackspot sharks are also caught on longlines, and some of the sharks from this study may have come from these fisheries, although the trader viewed that most come from handline fisheries. Longlines can stretch between 100 m and 1 km, set at 10–30 m deep, and it is the bottom-set longlines (called ‘rawai’) that tend to catch blackspot sharks. Because the longlines are left at sea for longer periods, the sharks are often deceased when hauled in, and the stress of pulling the longline up from depth can also cause mortality. Longline fisheries use fish of lower market value as bait, such as sardines and eel flesh. Eel flesh has tough skin and stays on the hook even if smaller fish bite at it. Any blackspot sharks caught are landed on nearby Indonesian islands. The sharks are eaten locally in Indonesia for their meat, but if there is a demand in Singapore they will be imported into the country via the two fishery ports (Jurong Fishery Port and Senoko Fishery Port).

Fig. 10.

Catch location of 92 blackspot sharks (Carcharhinus sealei) sourced from a private seafood supplier who is based in Singapore. The sharks were caught in Indonesia (in the Riau Islands; an island chain close to Singapore) from a handline fishery predominantly targeting other species of fish, located approximately at the marker (red star). The upper right box highlights the catch area relative to other countries in the region.

Interview: the Singaporean market for blackspot sharks

Within Singapore, blackspot sharks from this supplier are usually sold whole in wet markets (primarily Tekka market), with Singapore’s Indian population reportedly being the main buyers, who tend to cook it in curries for personal, domestic use. Historically, blackspot sharks have always been used for their meat, which is considered superior to other species (such as bull shark and blacktip sharks) because it is softer; however, overall, the supplier reported that shark meat has never been a particularly large or prominent part of the Singaporean diet. The supplier stated that supply and demand of blackspot sharks has reduced over the years and is attributed to (a) lower population numbers and fewer being caught, and (b) increased availability of substitutes, including imported frozen blue shark meat, which is more convenient because whole, fresh sharks (such as blackspot sharks from Indonesia) have to be processed. Blackspot sharks contribute less than 5% of the supplier’s business and he reported that ‘not catching and selling it would not impact me’, and that the market is too small to warrant it being directly ‘replaced’ by another species if it could not be caught or sold.

Interview: population trends and management options

The supplier has observed a decline in the availability of blackspot sharks over the years, estimating this decline at 50–70% over his 45 years in the industry. Blackspot sharks could reportedly be caught from the shore before, but now this was not the case. The species tend to be caught during monsoon seasons (approximately November, December, as well as in June), and he suspected this is when they aggregate for breeding. Outside of monsoon seasons, the catch is more sporadic. The supplier thought that blackspot sharks would benefit from improved management. Although the release of blackspot sharks caught could be an option, because they have relatively low market value compared to other seafod species, the supplier highlighted some challenges; for example, fishermen would still pull the shark on board to remove their hook, and this rough handling on-board could result in high post-release mortality. Cutting the line while the shark is still in the water would reduce this stress; however, fishermen may be unwilling to do this as they will lose the hook. If the sharks were released in such a manner, he recommended that research assess post-release survival rates. For the longline fisheries, most sharks are dead when hauled in; so, release of individuals is not an option under current fishing practices. However, as long as an animal has even a small market value, fishermen would want to retain and sell them. The supplier thought that more Marine Protected Areas with proper enforcement would be beneficial. Although requiem sharks, which includes blackspot sharks, have been added to supplementary appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES, as of November 2022), thus regulating their trade, the supplier stated that enforcement was an issue, and that regulation of trade does not necessarily stop animals being caught in the first place, particularly for species primarily caught incidentally, such as the blackspot shark.