Chiang Mai J. Sci. 2021; 48(5) : 1259-1270http://epg.science.cmu.ac.th/ejournal/Contributed Paper

Contributions of Seagrasses and other Sources to Sea Cucumber Diets in a Tropical Seagrass EcosystemAdonis Floren [a,b], Ken-ichi Hayashizaki [c], Piyalap Tuntiprapas [d] and Anchana Prathep*[d][a] Seaweed and Seagrass Research Unit, Division of Biological Science, Faculty of Science, Prince of Songkla

University, Hat Yai 90112 Thailand[b] Silliman University-Institute of Environmental and Marine Sciences, Bantayan, Dumaguete City 6200, Negros

Oriental, Philippines[c] School of Marine Biosciences, Kitasato University, Kitasato, Minami-ku, Sagamihara, Kanagawa 253-0373

Japan[d] Excellence Centre for Biodiversity of Peninsular Thailand, Division of Biological Science, Faculty of Science,

Prince of Songkla University, Hat Yai 90112 Thailand*Author for correspondence; e-mail: anchana.p@psu.ac.th

Received: 4 October 2020Revised: 16 April 2021

Accepted: 27 April 2021

ABSTRACT A study was conducted to determine the fractional contributions of seagrasses and other

sources to the sediment and the diet of the sea cucumbers Holothuria scabra and H. atra-leucospilota in a tropical seagrass meadow. The contribution from each source was estimated using the MixSIAR mixing model wherein the trophic enrichment factors of communities were integrated in the model. The results of the study suggest that the seagrass contribution to the sediment was coupled with the sea cucumber diet. Seagrass species contributed 32.0 % of the organic matter in the sediment while the contributions from the land plants, mangroves, microphytobenthos, coastal particulate organic matter, river particulate organic matter were 15.0, 14.4, 14.3, 13.2, and11.0 %, respectively. Subsequent assimilation of these sources by the sea cucumbers H. scabra and H. atra-leucospilota revealed that 61-70 % of their diet was derived from the seagrasses. This finding suggests these two sea cucumbers shared similar diet sources in the meadow as reflected in the similarity of proportional contributions of sources to their diets. The implications of this study may help in the conservation of sea cucumbers due to the destruction of seagrass habitats in many parts of the Southeast Asian region.

Keywords: stable isotope, seagrasses, sediments, sea cucumbers, MixSIAR

1. INTRODUCTIONTropical seagrass meadows are productive

ecosystems that support diverse populations of animals, including sea cucumbers. The close association between sea cucumbers and seagrasses has been documented in several studies [1-6] although little is understood about the dependency

of sea cucumbers on seagrasses with the use of stable isotopes. The estimation of the contribution of seagrasses to sea cucumber diets through the detritus-based pathway is vital to our understanding of the trophic relationships in these communities. An experimental study conducted in a flow-through

Chiang Mai J. Sci. 2021; 48(5)1260

system revealed that the detritus of the eelgrass Zostera marina Linnaeus, 1753 had a great influence on the growth of the sea cucumber Apostichopus japonicas [7]. In addition, tissues of Posidonia oceaninca (Linaeus) Delile, 1813 were found to dominate the diets of holothurians, which play a key role in nutrient recycling [8-9]. In recent year, Belbachir et al [10] showed that the contribution of P. ocenanica detritus to the diet of temperate sea cucumbers was lower in the degraded seagrass meadow as compared to that in the undisturbed meadow. The sea cucumbers H. scabra and H. atra are two of the most commonly harvested species of sea cucumbers in the tropical seagrass meadows and are currently on the IUCN red lists of endangered and least concern species, respectively [11-12]. The populations of the sea cucumber H. scabra are already completely decimated in many coastal areas due to the selective harvesting of this species in the wild [12-13].

Measuring the contribution of seagrasses to organic matter in the sediment is the first crucial step to understanding the dietary source for sea cucumbers because sea cucumbers are typically deposit feeders. On the southwest coast of Thailand, the contribution of seagrasses to the sediments was estimated at 36-42% using a Monte Carlo simulation [14]. However, a recent estimation of the contribution of seagrasses to sediment organic matter using Bayesian stable isotope analysis in R (SIAR) revealed a sharp contrast in the estimates, with values of ~13.2 %, indicating potential overestimation of the previous data [15]. Resolving the variability in model outputs requires in-depth investigations using more recent findings, which suggest much higher (50-52%) contributions from seagrasses to the sediments in restored or natural seagrass meadows [16-17]. In the tropical region alone, the seagrass-derived carbon stored in sediments varies greatly from 4-34% depending on the location [18]. It is therefore crucial for researchers who plan to use mixing models to obtain an accurate estimate of trophic enrichment factors because quantitative

diet estimates can help direct future research or prioritize the conservation and management of sea cucumbers [see 19].

In Libong Bay, Southwestern Thailand, many species of sea cucumbers coexist in the same seagrass meadow, and these various species potentially utilize similar food sources. The sea cucumbers H. atra and H. leucospilota also share gross features so that distinguishing between the two species in the field was a daunting challenge; thus, the two species were combined and hereafter referred to as H. atra-leucospilota complex or simply H. atra-leucospilota. This scenario provides a unique venue to estimate the contributions of seagrasses and other sources to the diets of sea cucumbers using a diet mixing model. However, one difficulty in using a mixing model is that some samples cannot be solved as they violate some of the implicit assumptions, such as the existence of degradation processes that have altered the isotopes [20]. Belbachir et al. [10] suggested that it would be necessary to experimentally determine the fractionation factors (enrichment factors) between the sea cucumbers and its diet for the isotope mixing model. However, unlike the feeding experiments conducted on animals that readily feed on fresh plant and/or animal tissues [e.g., 21-23], the determination of enrichment factors between the sea cucumbers and seagrasses requires that animals have to be reared in conditions with consistent diet of decaying seagrasses, although the stable isotope values of which vary depending on the stage of decomposition [see 24]. Thus, estimating the contribution of seagrasses and other sources to the diet of sea cucumbers based on the isotope values of fresh seagrasses may be insufficient until it has been adjusted for the effect of decomposition. This study addressed the abovementioned commentary by integrating the decay factors of the diet sources whenever available and the enrichment factors of the consumers in the MixSIAR mixing model to reflect the trophic conditions in the wild. The potential food sources for sea cucumbers considered in the mixing

Chiang Mai J. Sci. 2021; 48(5) 1261

model are seagrasses (SG), mangroves (MG), river particulate organic matter (RPOM), coastal particulate organic matter (CPOM), land plants (LP) and microphytobenthos (MPB). Although there were limitations in the sampling regimes, this study revealed the information about the possible food sources of tropical sea cucumbers, which have premier importance for the conservation of these species.

2. MATERIALS AND METHODS2.1 Study Site

This study was conducted in Libong Bay, which is located on the Southwestern side of Libong Island, Trang Province, Thailand (Figure 1). The coastline of Libong Bay is only approximately 8 km long, and the intertidal area extends approximately 1 km offshore. The seagrass meadow within Libong Bay is estimated to be approximately

Figure 1. Map of Libong Bay in Trang Province, Thailand, where the sea cucumbers, sediments, and seagrasses were collected at three representative locations (●). Sampling locations for RPOM (♦) and CPOM (◊) obtained from Stankovic et al. (2021), the Mangroves (◙) and Land Plants (■) from [14], and MPB (▲) from [15].

Chiang Mai J. Sci. 2021; 48(5)1262

5 km2 in size and is mostly dominated by Enhalus acoroides and Halophila ovalis in the intertidal areas, while the subtidal area is mainly composed of H. ovalis [25]. The seagrasses E. acoroides, Thalassia hemprichii and H. ovalis are of special interest in this study since they have been associated with the occurrence of certain sea cucumber species in many tropical seagrass meadows [1-5]. Water visibility in the seagrass meadow is typically low at < 1 m, such that data collection could only be undertaken during low tides at the intertidal area.

2.2 Collection of SamplesA survey was conducted from July 3 to July 5,

2017, at three representative locations of Libong Bay (Figure 1) where the sea cucumbers H. scabra and H. atra-leucospilota were reportedly thriving. A group of 5-7 persons exhaustively searched for sea cucumbers at low tides for 2-3 hours at each location. Adult sea cucumbers (≥150 g wet weight), seagrass leaves and sediment samples were collected in a non-quantitative manner due to the extremely low population densities at 1-2 individuals per 3 ha. The adult weight category was assumed to have a minimal influence on the isotope values of the sea cucumbers after our preliminary field trials indicated that the isotope values of the much smaller H. scabra juveniles (5-10 g wet weight) already resembled close to the seagrass H. ovalis value (i.e., δ13C = -16.0 ‰, δ15N = 6.2 ‰ and δ13C = -14.7 ‰, δ15N = 4.6 for juvenile H. scabra and H. ovalis, respectively) after a 40-day culture period in the H. ovalis meadow [see 26-27] for reviews on trophic enrichment and turnover rate estimations). In addition, the influence of gleaning activities on the abundance of sea cucumbers was not considered in this study due to the fact that Libong Bay is a protected zone such that sea cucumbers have some degree of protection from the commercial harvesting of sea cucumbers. However, local residents are only allowed to gather sea cucumbers for subsistence. Once a sea cucumber was encountered, mature seagrass leaves and sediment samples within

the vicinity (1-5 m) of the sea cucumbers were collected and brought to the laboratory for processing. Sediments from the top 5 cm surface were collected using a plexiglass corer (4.4 cm diameter) and transferred to sealed plastic bags for transport. In terms of substrate preference, it was already shown in the preliminary study that H. scabra adults were found in the seagrass meadows with significantly higher silt fractions of 27.5 % as compared to that of H. atra which had 17.5 %. Lumping of samples was also necessary due to the limited number of sea cucumbers in the area. All samples were transported back to the laboratory on ice and stored in a freezer at -20° C until processing. 2.3 Stable Isotope Measurement

To prepare for stable isotope analysis, epiphytes were removed from the mature green leaves of seagrasses using a gentle brush, and the leaves were then rinsed with distilled water. Calcareous epiphytes attached to the leaves were removed using a scalpel. The internal organs were removed from the sea cucumber samples, and the samples were then rinsed with distilled water. Only the muscular (body wall) tissues of the sea cucumbers were processed for isotopic measurements since the main objective of this study was to provide a basic understanding on the trophic interaction between the seagrasses and sea cucumbers via the sediments and not so much on the specific metabolic or tissue-related effects in the food web.

All samples, including the sediments, were dried in an oven at 55°C to constant weight and ground to fine powder using a mortar and pestle. Sediments and sea cucumber muscle samples were treated with 1 N HCl to remove the calcium carbonates from the sample following the method of [28]. Three (3) replicate samples from each seagrass species (i.e., H. ovalis, T. hemprichii and E. acoroides), consumers (i.e., H. scabra and H. atra-leucospilota) and sediments were processed for isotopic measurements.

Chiang Mai J. Sci. 2021; 48(5) 1263

Information on the isotope values of RPOM (Trang River mouth) and CPOM were obtained from a parallel study of Stankovic et al. [29] which was done in conjunction with this study (Figure 1). The data on LP, MG and MPB were extracted from extensive studies conducted in Trang Province, Thailand [14-15]. The average isotope value of mangrove leaves collected along the Trang riverside and National Park [14] was taken as an input for the model since the buoyant leaves are easily transported by ocean currents in the same manner that mangrove propagules were dispersed across the wide Indian Ocean from the various points of origin [30].

The isotope profiles (δ13C, δ15N) of seagrass leaves (E. acoroides, H. ovalis, and Thalassia hemprichii), H. scabra, H. atra-leucospilota and sediments (top 5 cm surface) were determined by an isotope-ratio mass spectrometer (Thermo/Finnigan Delta plus XP) coupled with an elemental analyser, and all isotopic analyses were performed at Kitasato University, Japan.

Values of isotopic analyses were expressed as:δ13C or δ15N = [(Rsample/Rstandard) –1] × 1000,

where Rsample and Rstandard are the 13C/12C or 15N/14N ratios of the sample and standard, respectively. The standards were Pee Dee Belemnite limestone and atmospheric air for carbon and nitrogen, respectively. The units are expressed as per mil (‰), and the sensitivity of the machine was 0.5 ‰ and 0.1 ‰ for δ13C and δ15N, respectively.

2.4 Isotope Mixing Model The Bayesian mixing model stable isotope

analysis in R (MixSIAR) [31] was used to estimate the contributions of the SG, MG, LP, RPOM, CPOM and MPB to the sediments and the diet of the sea cucumbers H. scabra and H. atra-leucospilota. This model was developed to estimate the probability distributions of source contributions to a mixture while explicitly accounting for uncertainty associated with multiple sources, fractionation and isotope

signatures; and to allow for optional incorporation of informative prior information [32]. MixSIAR is particularly suitable in the present data set as it incorporates the decay and enrichment factors of communities resulting in the accurate estimate of the source contributions.

The contributions of the seagrass E. acoroides, H. ovalis, and T. hemprichii to the sediments were determined for each seagrass species. Subsequent combination of these 3 seagrass species was necessary in order to determine the overall contribution of the seagrass community to the sediment. The contribution of the source to the sediment was considered important when the value was >5.0%, as suggested by Phillips et al [33]). Prior to performing the mixing model simulation, the stable isotope value of each seagrass species was adjusted based on the average decay factors of seagrass over time at -0.8 and -1.4 ‰ for the δ13C and δ15N values, respectively [24]. Averaging the decay factors of seagrass was necessary since the sea cucumbers are assumed to feed on the newly decomposed and mineralized seagrass components. Additionally, the isotope values of Mangroves were adjusted by 0.9 ‰ and -0.9 ‰ for the δ13C = -16.0 ‰, δ15N, respectively, based on the average decay factors indicated by Fourqurean and Schrlau [24]). Similarly, the isotope values of the Land Plants were adjusted following that of Mangroves as they were assumed to have similar decay rates. However, there were no adjustments made on the stable isotope values of MPB considering that these sources are known to be consumed by the sea cucumbers alive. Finally, there were also no adjustments made on the stable isotope values of CPOM and RPOM due to the absence of decay factors for these sources in the literatures. After the decay and fractionation factors were applied, the MixSIAR model was run through 1 × 106 iterations.

The diet sources available for the diets of H. scabra and H. atra-leucospilota were represented by the eight end-member sources in the model. Each seagrass species was treated as a separate

Chiang Mai J. Sci. 2021; 48(5)1264

source considering the close association of sea cucumbers with specific seagrasses [1, 34]. The TEF for the H. scabra mixture was adjusted by 1.5 and 2.4 ‰ for the δ13C and δ15N, respectively. These adjustments were based on the trophic enrichment factors obtained from the controlled feeding experiments on the juvenile H. scabra [35]. In addition, the δ15N value of the bulk body wall (i.e., body wall containing the spicules) of the juvenile H. scabra was used in the model due to the observed effect of acid treatment on δ15N values. 3. RESULTS AND DISCUSSION3.1 Stable Isotope Profiles

The stable isotope ratios (δ13C, δ15N) of the sea cucumbers H. scabra and H. atra-leucospilota and the sources E. acoroides, T. hemprichii, H. ovalis, CPOM, RPOM, MG, LP, and MPB showed distinct values (Table 1). In terms of the δ13C

ratio, H. scabra had a slightly higher value than H. atra-leucospilota, which differed by only 1.1 ‰. On the other hand, H. atra-leucospilota had a higher δ15N ratio than H. scabra, which differed by 2.3 ‰. In general, both sea cucumbers had δ13C values comparable to those of the seagrasses, but there was a marked increase in the δ15N values of sea cucumbers compared to the seagrasses. The seagrasses were most enriched (highest) in δ13C compared to the other sources, with values reaching up to -10.6 ‰ for E. acoroides. Increases in the δ13C and δ15N ratios were also observed among the seagrasses, with E. acoroides being the most enriched in terms of δ13C, while H. ovalis was most enriched in δ15N. The CPOM and MPB had relatively similar δ13C ratios at -21.6 and -20.7 ‰, respectively, which also comprised the organic materials in the sediment. The δ15N ratios for CPOM and RPOM seagrasses were

Table 1. Mean, standard deviation (SD), number of replicates (n) of δ13C and δ15N ratios for the mixtures and sources from the seagrass meadow of Libong Island, Trang Province, Thailand. CPOM, coastal particulate organic matter; RPOM, river particulate organic matter.

Sampleδ 13C (‰) δ 15N (‰)

n Mean SD Mean SD

Consumer / Mixture

Holothuria atra- leucospilota 3 - 12.0 0.8 7.5 1.2

Holothuria scabra 3 - 10.9 0.5 5.2 0.4

Sediment 3 - 21.4 1.4 1.8 0.3

Sources

Enhalus acoroides 3 - 10.6 1.5 3.8 0.9

Halophila ovalis 3 - 14.7 1.9 4.6 0.9

Thalassia hemprichii 3 - 13.0 2.8 4.0 0.7

CPOM* 12 - 21.6 1.1 6.2 1.5

RPOM* 3 - 24.6 0.2 6.1 1.6

Mangroves** 6 - 27.0 1.4 2.8 2.3

Land plants** 8 - 28.9* 1.5 - 0.5 1.2

Microphytobenthos*** 3 - 20.7 0.2 0.1 0.2* Stankovic et al. (2021)**Kuramoto and Minigawa (2001)*** Kon et al. (2015)

Chiang Mai J. Sci. 2021; 48(5) 1265

the most enriched sources of δ15N, with values reaching as high as 6.2 ‰ for CPOM.

3.2 Contribution to the SedimentAdjustment on the mixing model parameters

using the seagrass decay factors of -0.8 and -1.4 ‰ for the δ13C and δ15N values, respectively, revealed that the origin of organic matter in the sediment of Libong Bay was primarily derived from the seagrasses E. acoroides (10.4%), T. hemprichii

(10.7%) and H. ovalis (10.9%) with a combined contribution of 32.0% (Figures 2(a) and 3 (a)). The contributions from MPB, MG, CPOM, RPOM and LP were in the range of 11.0- 15.0 %, all of which were important to the sediment having contributed >5.0% to the organic matter. This finding is reflective of a previous study conducted along the southwest coast of Thailand, where the contribution of seagrasses to the sediments was estimated to be 36.0 % [14]. Although these

Figure 2. Biplot of δ 13C and δ 15N for the sediment (a) that were represented with grey circles and the seacucumbers (b) on the potential sources e.g., seagrasses E. acoroides (Ea), H. ovalis (Ho), T. hemprichii (Th), coastal particulate organic matter (CPOM), river particulate organic matte (RPOM), mangroves (MG), microphytobenthos (MPB), and land plants (LP) after the incorporation of decay factor (see in the text).

Chiang Mai J. Sci. 2021; 48(5)1266

estimates were approximately two-fold higher than those reported in the more recent publication by Kon et al [15], much higher contributions of up to 50-52% were reported from restored or natural seagrass meadows [16-17]. The close similarity of the present finding with that of Kuramoto and Minagawa [14] emphasizes the importance of incorporating the decay factors of sources in the mixing model, which provides a detailed understanding of the decomposition process occurring in the sediment. Although the δ15N values of sediments in the present study were lower by ~ 2.0 ‰ as compared to that of [14], the variation could be attributed to the sampling regimes since the latter sediment samples were collected at the deeper subtidal areas of Libong Bay, such that the decomposition of organic material may have occurred at a slower rate with the increase in sampling depth [37]. Similarly, the higher contributions of MG and LP to the sediments in the study of Kuramoto and Minagawa [14] as compared to the present study may be explained by the continuous supply of these materials in the subtidal areas regardless of the tidal cycles. Thus, the adjustments made to the mixing model parameter may also help explain the variability in model outputs within the Southeast Asian region.

The variation in the fractional contributions of sources to the sediment may also be influenced by environmental factors such as the trapping of particulate materials [36-37], proximity to autotrophic sources [38], vegetation coverage [20], seagrass biomass production [39], and degradation of marine macrophytes [40]. For example, the high contribution of the seagrasses to the sediment may be attributed to the high density and growth rates of the seagrasses such as E. acoroides in this part of Southeast Asia [41]. Additionally, the contribution of mangrove leaves may be lower than that of seagrasses since most mangrove leaves are typically buoyant and easily transported by ocean currents, whereas the leaves of the seagrass E. acoroides sink soon after shedding [42]. Overall, the contribution of sources to the

sediment reflects the important contributions of the nearby communities located in tropical ecosystems.

3.3 Contribution to the Sea Cucumber DietsIn the case of the sea cucumbers, the diets of

H. scabra and H. atra-leucospilota were also primarily derived from the seagrasses E. acoroides (25-28 %), T. hemprichii (20-25 %) and H. ovalis (16-17 %) with a combined contributions ranging 61-70% (Figures 2 (b) and 3). However, a distinctly higher contribution from the seagrass E. acoroides as compared to other species was discernible. The contributions from CPOM, RPOM, MG, LP and MPB were all considered important to the diet of H. scabra having contributed 6-10 % to its diet. A similar pattern was observed for H. atra- leucospilota except only for the land plants which contributed 4.0 % (or < 5.0 %) to the diet of this species. The implication of this finding suggests that H. scabra and H. atra-leucospilota may share similar food sources in the meadow as reflected by the similarity in proportional contributions of sources to the diet of both sea cucumber species. The greater assimilation of E. acoroides by these sea cucumbers may also be attributed to the higher abundance of the seagrasses such as E. acoroides in the intertidal areas as compared to the other seagrass species [25, 43].

The important contribution of temperate seagrasses to the diet of sea cucumbers has been demonstrated in the seagrass meadows of the Mediteranean [9, 44]. However, the incorporation of decay and trophic enrichment factors in the Bayesian mixing model framework was a prerequisite in order to accurately estimate the contribution of sources to the diet of consumers. This study provided an accurate estimation on the important contribution of the seagrasses and other sources to the organic matter in the sediment and the subsequent assimilation by the sea cucumbers H. scabra and H. atra-leucospilota in a tropical seagrass meadow.

Chiang Mai J. Sci. 2021; 48(5) 1267

19

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

Figure 4. Box plots showing the fractional contribution from each source to the (a) sediment, (b) H. 485

scabra and (c) H. atra-leucospilota, estimated using the mixing model (MixSIAR). Box plots illustrate 486

the 25th percentiles, mean and 75th percentiles, respectively. While whiskers indicate the 2.5th and 97.5th 487

percentiles. The sources abbreviation: Ea, Th, Ho, LP, MG, MPB, RPOM and CPOM are represent as 488

Frac

tiona

l con

trib

utio

n

19

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

Figure 4. Box plots showing the fractional contribution from each source to the (a) sediment, (b) H. 485

scabra and (c) H. atra-leucospilota, estimated using the mixing model (MixSIAR). Box plots illustrate 486

the 25th percentiles, mean and 75th percentiles, respectively. While whiskers indicate the 2.5th and 97.5th 487

percentiles. The sources abbreviation: Ea, Th, Ho, LP, MG, MPB, RPOM and CPOM are represent as 488

Frac

tiona

l con

trib

utio

n

Figure 3. Box plots showing the fractional contribution from each source to the (a) sediment, (b) H. scabra and (c) H. atra-leucospilota, estimated using the mixing model (MixSIAR). Box plots illustrate the 25th percentiles, mean and 75th percentiles, respectively. While whiskers indicate the 2.5th and 97.5th percentiles. The sources abbreviation: Ea, Th, Ho, LP, MG, MPB, RPOM and CPOM are represent as E. acoroides, T. hemprichii, H. ovalis, land plants, mangroves, microphytobenthos, river particulate organic matter, and coastal particulate organic matter, respectively.

Chiang Mai J. Sci. 2021; 48(5)1268

4. CONCLUSIONSThe incorporation of the decomposition

and trophic enrichments factors in the MixSIAR model has allowed this study to accurately estimate the contributions of various sources to the sediment and the diet of sea cucumbers. This coupling of seagrass decomposition with the diet of sea cucumbers provide an empirical evidence of the trophic interactions between the tropical sea cucumbers and seagrasses. Given the high contribution of seagrasses to the diet of H. scabra and H. atra-leucospilota, it is likely that both species are vulnerable to depletion due to the destruction of seagrass habitats in many parts of the Southeast Asian region. This study serves only as a base guideline for the restoration of sea cucumbers using the advent of stable isotopes. Further research is needed to expand our understanding on the spatio-temporal variations associated with tropical environments.

ACKNOWLEDGEMENTSWe thank Dr. M. Stankovic for the comments

and suggestions. This research was supported by the Higher Education Research Promotion and Thailand’s Education Hub for Southern Region of ASEAN countries Project Office of the Higher Education Commission. The research was also partly supported by the Center of Excellence on Biodiversity, Office of Higher Education Commission, grant No. BDC-PG3-160017 to AP. This work was partially supported by the JSPS Core-to-Core Program CREPSUM JPJSCCB20200009. The SSRU, Graduate School of Prince of Songkla University and Silliman University are gratefully acknowledged. The licence to use animals for scientific purposes, ID U1-07888-2561, was provided by the Institute of Animals for Scientific Purpose Development (IAD), National Research Council of Thailand (NRCT).

REFERENCES[1] Mercier A., Battaglene S.C. and Hamel J.F., J.

Exp. Mar. Biol. Ecol., 2000b; 249(1): 89-110.

DOI 10.1016/S0022-0981(00)00187-8.

[2] Dance S.K., Lane I. and Bell J.D., Aquaculture, 2003; 220(1-4): 495-505. DOI 10.1016/S0044-8486(02)00623-3.

[3] Dissanayake D.C.T. and Stefansson G., J. Mar. Biol. Assoc. UK, 2012; 92(3): 581-590. DOI 10.1017/s0025315411000051.

[4] Hair C., Mills D.J., McIntyre R. and Southgate P.C., Aquac. Rep., 2016; 3: 198-208. DOI 10.1016/j.aqrep.2016.03.004.

[5] Hartati R., Trianto A. and Widianingsih, IOP C. Ser. Earth Env., 2017; DOI 10.1088/1755-1315/55/1/012041.

[6] Ceccarelli D.M., Logan M. and Purcell S.W., Mar. Ecol. Prog. Ser., 2018; 588: 85-100. DOI 10.3354/meps12444.

[7] Liu X., Zhou Y., Yang H. and Ru S., PLoS ONE, 2013; 8(3): 2-7. DOI 10.1371/journal.pone.0058293.

[8] Mazzella L., Buia M.C., Gambi M., Lorenti M., Russo G.F., Scipione M.B. and Zupo V., Plant-Animal Trophic Relationships in the Posidonia oceanica Ecosystem of the Mideteranean Sea: A Review; in John D.M., Hawkins S.J. and Price J.H., eds., Plant-Animal Interactions in the Marine Benthos, Clarendon Press, Oxford, 1992: 165-187.

[9] Lepoint G., Nyssen F., Gobert S., Dauby P. and Bouquegneau J.M., Mar. Biol., 2000; 136(3): 513-518. DOI 10.1007/s002270050711.

[10] Belbachir N.E., Lepoint G. and Mezali K., Belg. J. Zool., 2019; 149(1): 95-106. DOI 10.26496/bjz.2019.32.

[11] Conand C., Gamboa R. and Purcell S.W., The IUCN Red List of Threatened Species, 2013; DOI 10.2305/IUCN.UK.2013-1.RLTS.T180421A1628832.en.

[12] Hamel J.-F., Mercier A., Conand C., Purcell S., Toral-Granda T.-G. and Gamboa R., The

Chiang Mai J. Sci. 2021; 48(5) 1269

IUCN Red List of Threatened Species, 2013. DOI 10.2305/IUCN.UK.2013-1.RLTS.T180257A1606648.en.

[13] Eriksson H. and Clarke S., Biol.Conserv., 2015; 184: 163-173. DOI 10.1016/j.biocon.2015.01.018.

[14] Kuramoto T. and Minagawa M., J. Oceanogr., 2001; 57: 421-431. DOI 10.1016/j.jembe.2014.08.008

[15] Kon K., Tongnunui P. and Kurokura H., Food Webs, 2015; 2: 10-17. DOI 10.1016/j.fooweb.2015.03.001.

[16] Kennedy H., Beggins J., Duarte C.M., Fourqurean J.W., Holmer M., Marbá N. and Middelburg J.J., Global Biogeochem. Cy., (2010); 24(4): 1-8. DOI 10.1029/2010GB003848.

[17] Greiner J. T., Wilkinson G.M., McGlathery K.J. and Emery K.A., Mar. Ecol. Prog. Ser., 2016; 551: 95-105. DOI 10.3354/meps11722.

[18] Miyajima T., Hori M., Hamaguchi M., Shimabukuro H., Adachi H., Yamano H., and Nakaoka M., Global Biogeochem. Cy., 2015; 29: 397-415. DOI 10.1002/2014GB004979.

[19] Bond A. and Diamond A., Ecol.Appl., 2011; 21(4): 1017-1023.

[20] Gillis L., Ziegler A., Oevelen D., Cathalot C., Herman P., Wolters J. and Bouma T., PLoS ONE, 2014; 9(11). DOI 10.1371/journal.pone.0111847.

[21] Fry B., Stable Isotope Ecology, Springer, New York, 2006.

[22] Tieszen L., Boutton T., Tesdahl K and Slade N., Oecologia, 1983; 57: 32-37.

[23] McCutchan J.H., Lewis W. M., Kendall C. and McGrath C.C., Oikos, 2003; 102(2): 378-390. DOI 10.1034/j.1600-0706.2003.12098.x.

[24] Fourqurean J. and Schrlau, Chem. Ecol., 2003; 19: 373-390. DOI 10.1080/02757540310001609370

[25] Khogkhao C., Hayashizaki K., Tuntiprapas P. and Prathep A., ScienceAsia, 2017; 43(6): 339-346.

DOI 10.2306/scienceasia1513-1874.2017.43.339.

[26] Post D.M., Ecology, 2002; 83(3): 703-718. DOI 10.2307/3071875 .

[27] Zanden M.J., Vander Clayton M.K., Moody E.K., Solomon C.T. and Weidel B.C., PLoS ONE, 2015; 10(1): 1-16. DOI 10.1371/journal.pone.0116182.

[28] Bunn S.E., Loneragan N.R. and Kempster M.A., Limnol. Oceanogr.,1995; 40: 622-625. DOI 10.4319/lo.1995.40.3.0622.

[29] Stankovic M., Hayashizaki K.I., Tuntiprapas P., Rattanachot E. and Prathep A., Mar. Pollut. Bull., 2021; 163. DOI 10.1016/j.marpolbul.2020.111913

[30] Stocken T., Van Der, Carroll D., Menemenlis D., Simard M. and Koedam N., Proc. Natl. Acad. Sci., 2019; 116(3): 915-922. DOI 10.1073/pnas.1812470116.

[31] Stock B.C., Jackson A.L., Ward E.J., Parnell A.C., Phillips D.L. and Semmens B.X., PeerJ, 2018; 6: e5096. DOI 10.7717/peerj.5096.

[32] Moore J.W. and Semmens B.X., Ecol. Lett., 2008; 11 (5): 470-480. DOI 1111/j.1461-0248.2008.01163.x.

[33] Phillips D.L., Inger R., Bearhop S., Jackson A. L., Moore J.W., Parnell A.C., et al., Can. J. Zool., 2014; 92(10): 823-835. DOI 10.1139/cjz-2014-0127.

[34] Palomar-Abesamis N., Abesamis R.A. and Juinio-Meñez M.A., Aquat. Ecol., 2017; 51: 17-31. DOI 10.1007/s10452-016-9591-2.

[35] Watanabe S., Kodama M., Sumbing J.G. and Lebata-Ramos M.J.H., Jpn. Agric. Res. Q., 2013; 47(1): 127-134. DOI 10.6090/jarq.47.127.

[36] Agawin N.S.R. and Duarte C.M., Estuaries, 2002; 25(6 A): 1205-1209. DOI 10.1007/BF02692217.

[37] Panyawai J., Tuntiprapas P. and Prathep, A., Ecol. Res., 2018; DOI 10.1111/1440-1703.1066.

Chiang Mai J. Sci. 2021; 48(5)1270

[38] Connolly R.M. and Waltham N.J., Ecosphere, 2015; 6 (9): 1-12. DOI 10.1890/ES14-00243.1.

[39] Stankovic M., Panyawai J., Jansanit K., Upanoi T. and Prathep A., Sains Malays., 2017; 46(9): 1441-1447.

[40] Trevathan-Tackkett S., Kelleway J., Macreadie P., Beardall J., Ralph P. and Bellgrove A., Ecology, 2015; 96(11): 3043-3057.

[41] Rattanachot E. and Prathep A., Bot. Mar., 2011; 54: 201-207. DOI 10.1515/bot.2011.018.

[42] Mateo M.A., Cebrián J., Dunton K. and Mutcheler T., Carbon Flux in Seagrass Ecosystem; in Larkum A.W.D., Orth R.J. and Duarte C.M., eds., Seagrasses: Biology, Ecology and Conservation, Springer, Dordrecht, 2006: 159-192. DOI 10.1007/978-1-4020-2983-7_7.

[43] Kaewsrikhaw R., Ritchie R.J. and Prathep A., Aquat. Bot., 2016; 130: 11-20. DOI 10.1016/j.aquabot.2015.12.006.

[44] Costa V., Mazzola A. and Vizzini S., J. Exp. Mar. Biol. Ecol., 2014; 461: 226-232. DOI 10.1016/j.jembe.2014.08.008.