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App. Envi. Res. 41(3) (2019): 14-31

Applied Environmental Research

Journal homepage : http://www.tci-thaijo.org/index.php/aer

Trophic Models of in Maqueda Channel, Caramoan Peninsula, Philippines

Michael A. Clores1,2,3, Michael A. Cuesta1

1 Graduate School, Ateneo de Naga University, Naga City, 04400, Philippines 2 Natural Sciences Department, College of Science and Engineering, Ateneo de Naga University, Naga City, 04400, Philippines 3 Ateneo de Naga University Marine Biological Station, Barangay Tabgon, Caramoan, Camarines Sur, 04429, Philippines * Corresponding author: Email: [email protected]

Article History Submitted: 8 June 2019/ Revision received: 6 September 2019/ Accepted: 16 September 2019/ Published online: 7 October 2019

Abstract Steady-state trophic models were constructed using the Ecopath with Ecosim software to examine the general status, development trends, and functional integrity of three extensive seagrass located in Maqueda Channel of Caramoan Peninsula, Southern Luzon Island, Philippines. The results show that the ecosystems are composed of 23-24 functional groups with effective trophic levels extending from 1.00 to 3.76. Mixed trophic impacts show that decrease in the biomass of grazers Tripneustes gratilla (collector urchin) had a positive impact on the biomass of . On the other hand, a positive effect on the benthic groups is expected with an assumed decrease in the biomass of detritus and . Analysis of the flow network of organic matter and trophic efficiencies showed that flows were generally low for higher TLs but high for lower TLs (i.e., from TL 1 to IV. The ecosystems were found to be in mature and stable state based on the system statistics.

Keywords: Trophic models; Dynamic models; Seagrass systems; Caramoan Peninsula; Philippines

Introduction The seagrasses are important food source, Seagrass meadows, and coral habitats and refuges. Many populations of reefs are ranked almost equally in terms of and rely on seagrass meadows productivity [1-3] and provide numerous are their nursery grounds. Seagrass beds protect ecological goods and services [4]. These marine coastal habitats from extreme wave action, ecosystems are highly connected and support filters contaminants, and prevents sedimentation each other [5-6]. [1]. Seagrasses are classified as pioneer or

https://doi.org/10.35762/AER.2019.41.3.2 App. Envi. Res. 41(3) (2019): 14-31 15 climax based on the successional series meadows [12, 6]. Experiments showed that a along with the ranges of disturbance. For large quantity of aboveground biomass of instance, acoroides (tape or broad seagrass are consumed by grazers [13] yet most blade seagrass) is the South-East Asian species food webs of seagrass systems depicted that that best survive heavy siltation [7] while the only a small amount of seagrass material are small pioneer species are the first to recolonize assimilated [14]. This could be explained by barren areas [8]. the high rate of excretion but low rate of Tropical and subtropical waters are often assimilation of consumed seagrass material characterized by mixed-species meadows. Co- [15] as well as the temporal and spatial existing seagrass species likely show strong variability in the and biomass of the interactions because of their similar architecture seagrass-dwelling organisms [16]. and resource requirements. The mixed communities Marine ecologists are still grappling with represent steady-state communities in the the unresolved knowledge issues about the tropics caused by small-scale disturbance and energy flow depicted in seagrass food webs. positive interactions. Recurrent disturbance There is still a need to examine how much of appears to be a common feature essential to the production of seagrasses are incorporated maintenance of many seagrass beds [8]. into coastal food webs. Doing so could help Sedimentary processes like sand waves [9] or understand better the seagrass biotic disturbance including result in structure and the linkages that regulate the local perturbation that allows maintenance of component processes that are crucial for fast-growing species to dominate [10-11]. effective management of marine resources The positive interactions observed in [17]. Thus, a study that will elucidate through seagrass meadows involve the activity of modelling tools the energy fluxes within the species that modify the environment resulting food web in seagrass systems is very timely. in more suitable habitat to support plant life Such studies could provide a benchmark for and growth of other species. For example, future work on the ecosystem-based management when several species are eliminated as a approach and the basic knowledge about the consequence of problematic resource use, as key ecosystem metrics required in predicting observed in many Philippine mixed seagrass ecosystem change to less sustainable and meadows, the dominant species tend to imbalanced state. facilitate the development of denser populations Unresolved critical gaps of knowledge of the co-existing species [8]. This is due to between the contribution to seagrasses the oxygenation of sediments preventing incorporated in into coastal food webs call for accumulation of toxins that cause seagrass research using modelling approaches that when mortality [7]. Moreover, moderate disturbance confirmed by future studies, would have also allows maintenance of complex and insightful implications for our appreciation and diverse communities and spatial patterns, but understanding of ecosystem functioning and intense disturbance drastically reduce the required ecosystem-based management thereto. meadows [8]. The objective of this study was to use It has been established that the increased trophic modelling as tool, specifically the level of abundance and diversity of animals Ecopath with Ecosim and Ecospace (EwE) found in seagrasses are due to the productivity modelling approach [18] to express and simulate of seagrasses, intricacy of food webs, and trophic flows between various groups present complexity of the physical structure of the in the seagrass system to answer the question: 16 App. Envi. Res. 41(3) (2019): 14-31

What are the characteristics of the seagrass site (Site 1: Cagbanilad Bay, 13038’14”N ecosystem structure (i.e., components, links, and 123053’27”E, Site 2: Sabitang-laya Island, transfer efficiencies) and the flows of energy 13052’00”N 123051’32”E, and Site 3: Nipa and biomass in seagrass ecosystems? The Bay, 13057’51”N 123050’07”E) (Figure 1). models were utilized to examine the seagrass Data collection was conducted from June 2017 ecosystem structure and were used in analysing to March 2018. impacts on the biomass of organisms on the whole ecosystem. The results of the study 3) Sampling design provided information as basis for formulating A 20-cm corer was used in estimating the management goals for seagrass systems. Policy biomass of seagrasses and seagrass-associated makers, particularly the local government of macroinvertebrates. The corer collected Caramoan, may act on the research output to seagrasses with their substrate from an area of commence possible options for sustainable 0.031 m2. In Site 1: Cagbanilad Bay, the samples ecosystem interventions. were collected at five (5) transects oriented This study specifically aimed to estimate the perpendicular to the shoreline extending to basic building blocks of Ecopath models such about 25 m offshore across the seagrass as biomass, production, consumption rates, and . In Site 2: Sabitang Laya Island and diet for each defined functional group within a Site 3: Nipa Bay, ten (10) 50-m transects were defined model area and time, to describe the established in each of the two sites. impact of components, and to determine the A total of 115 core samples (15 samples in level of development and state of maturity of Site 1, 50 samples each in Site 2 and 3) were the ecosystems. collected from a point-to-point distance of ~5 m for Site. and ~10 m for Sites 2 and 3, Materials and methods perpendicular to the shoreline during each 1) Research design and approach sampling time. Collection of samples was done Extensive computer-based work to run mass- during the lowest tidal level for accuracy and balanced trophic modelling aided by the Ecopath ease of sampling, from at least 20-30 m starting with EwE software [19] was done to examine from the landwards edge of the seagrass bed. the trophic structure and development trends of A fine mesh bag (0.5 to 1.0 mm mesh) was the Caramoan seagrass ecosystems. This used to sieve the core samples while still in the involved the estimation of the basic building field. After sorting the seagrass and , blocks of Ecopath models such as biomass, these were identified to the lowest taxon, and production, consumption rates, and diet for then counted. Before obtaining the wet weights each defined functional group. Field work was (g ww m-2) of the seagrasses, these were scraped done to conduct standard sampling strategies using a razor blade to remove the epiphytes. on the functional groups in the seagrass The sturdy beam trawl sampler that provided a ecosystems in three sampling locations. sampling area of 50 m2 was used to collect epifauna (Raz-Guzman and Grizzle, 2001). Ten 2) Sample sites sampling efforts were done at daytime for Three locations at the Maqueda Channel, diurnal fauna and another ten at night time for Caramoan Peninsula, Southern Luzon Island, nocturnal fauna. The total wet weight biomass Philippines where extensive seagrass beds exist in g ww m-2 of each sample was converted to were selected for the study. In each location, t km-2. a was selected as study App. Envi. Res. 41(3) (2019): 14-31 17

Figure 1 Sampling sites: Cagbanilad Bay (Site 1), Sabitang-Laya Island (Site 2) and Nipa Bay (Site 3) in Maqueda Channel, Caramoan Peninsula.

4) Modelling approach Estimates of Biomass (B) per compartment The models for the three seagrass meadows were from actual field data, but most of the were constructed using Ecopath with EwE value of other parameters such as Productivity: version 6.2 [19]. The Ecopath food web models Biomass (P/B), Consumption: Biomass (Q/B), were constructed with biomass estimations of fraction of unassimilated food, and/or some 23 to 24 trophic groups and their prey and combined variable (e.g. Gross food conversion predators to determine an instantaneous mass Efficiency (GE as PB/QB), were based on balance description of the seagrass food web published literature. Biomass and P/B of structure and linkages. phytoplankton were based on Campos’ [29] No data on the diet of invertebrates in the derivation of initial estimates for phytoplankton study sites was available, hence diet items of using mean primary rates for Pacific shelf areas these functional groups were based on the (=0.52 g C m-2 d-1, Mann, 1982). P/B ratio of literature [20-22]. Diet compositions were seagrasses was based on Aliño et al.’s [23] estimated based on the relative abundance of initial estimates for seagrasses utilizing each prey in the study area. Moreover, if estimates of Fortes [30] of seagrass biomass reasonably applicable, the P/B (production/ (61.7 g organic matter m-2) and productivity biomass ratio for functional group) and Q/B (1.4 g C m-2 d-2). This is consistent with the (the ratio of the consumption to biomass for notion that P/B ratio provides a better predator) of certain marine organisms were indication of energy transfer between trophic derived from values reported from various levels than instantaneous measures of biomass. coastal ecosystems [23-27] (see Supplementary Populations of large, long-lived seagrass have a Material 1). greater biomass but lower production than the 18 App. Envi. Res. 41(3) (2019): 14-31 plankton, hence P/B ratio is relatively low for The functional groups which showed EEs seagrasses (low production, high biomass) and greater than 1 were suspected to have high for phytoplankton (high production, low underestimated biomass using the beam trawl biomass). net sampling tool, hence their biomasses were Probable diet and life history characteristics adjusted based on available literature (Table 1). were used as bases for the living compartments In the succeeding model runs, the EEs of some of taxa. For instance, for gastropod families functional groups, such as P. nodosus, known to be coral, and seagrass-eaters Diadema spp. (long-spined urchins), [31], their diet was estimated to be composed pelecypods, Synapta maculata (spotted worm of 10% of each of the seagrass species. sea cucumber), and other holothurians, were Gut content analysis was done to determine still more than 1. The models were still the diet composition of T. gratilla imbalanced, thus their P/Bs were adjusted, and [32]. The diet of asteroid Proteroaster nodosus as a final step, their biomasses were instead (horned sea star or chocolate chip sea star) was manually adjusted by gradually increasing or estimated based on literature that they prey on decreasing the values until the EE is less than 1. , bivalves, gastropods, and other large invertebrates [33]. Other trophic models 5) Data analysis and literature [34] were used for the diet The first set of analysis for the Ecopath composition of other groups. models of the seagrass systems is the structural Biomass, P/B, Q/B ratios, and diet composition analysis of the food webs which is based on all were entered as basic inputs to EwE while flows and biomasses that can be depicted in a biomass accumulation was set as zero. P/Q single flow diagram constructed by Ecopath. ratio and Ecotrophic Efficiency (EE) were The size of the circles is relative to biomass for estimated by the software. EE is the portion of each group. Circles are placed on the Y-axis the production of a group that is consumed based on the trophic level. The figure shows within the system and is the portion of the aggregation of the functional groups production exported or consumed by predators represented as discrete trophic levels, and the [35]. Trophic levels are part of the calculated estimation of the distribution of biomass and results. The diet compositions of groups were transfer efficiencies among trophic levels. The checked if the outputs differ from the figure can indicate the following: (i) main paths anticipated level. in the ecosystem, (ii) the degree of importance Initial models were not balanced because the of detrital and grazing food chains in the EEs of some functional were higher than 1 ecosystem, (iii) main sources for flow to suggesting that their demand was very high detritus, and (iv) where most a functional group [35-36]. Manual adjustments of the input was a main food source leading to the occurrence parameters, such as biomass and diet of most of flow the in the trophic web. composition were done to ensure that EE is less The second analysis on the Ecopath models than 1 to balance the model. This is to ensure of the seagrass systems was done by using that at the end of one year there is excess mixed trophic impact (MTI) routine [37]. MTI biomass that could accrue or transfer from the allows measurement of the impact of one system or lose by mortality [36]. Trophic functional group in the seagrass system on all models were finally balanced after integrating the other groups after a short period of variation. all the basic inputs and manual adjustments of Hence it can be considered as a form of biomass. sensitivity analysis for the seagrass models’ App. Envi. Res. 41(3) (2019): 14-31 19 input parameters. Network flows and ecosystem composed of 23-24 functional groups with attributes based on the seagrass system models effective trophic levels extending from 1.00 to were used to compare the status of seagrass 3.76. Thus, the seagrass system models were ecosystems and to characterize their scale, relatively similar in terms of the number of stability and maturity status. For instance, to compartments or functional groups with other characterize the ecosystem size and how ecosystems: 18 in the fringing reefs in Nanwan proportion of matter that the system processes, Bay (Taiwan) [42], 17 in the seagrass-benthic as reflected by the respiratory flows, flows to ecosystems in Tongoy Bay (Chile) [43], 26 in detritus, sum of consumption, and exports, the the Pearl River (China) [25] and 24 in the coral Total System Throughput (TST) index was reef flat ecosystems in Bolinao (Philippines) used [38]. An index of ecosystem maturity is [23]. The effective trophic values are also close the Total Biomass:TST ratio (B:TST) which is to the reported in the literature [23, 25, 42-43]. based on the fraction of biomass necessary to Producers such as phytoplankton and maintain one unit of flow. Two other indices of seagrasses, and the detritus are assigned to ecosystem maturity are the Net Primary trophic level TL = 1; the invertebrate groups Production: Respiration ratio (P:R) and the are placed in the second and/or third levels. Net :Total Biomass ratio Syngnathidae are in the maximum TL (TL = (P:B) To describe the maturity and intricacy of 3.76 for Cagbanilad Bay and 3.75 for Sabitang- the links inside the seagrass ecosystems, the Laya and Nipa bays), (TL = 3.46 for values computed by Ecopth for System Cagbanilad Bay and 3.45 for Sabitang-Laya Omnivory Index (SOI) and Connectance Index and Nipa bays), constitute the top predators in the (CI), which is anticipated to be higher in mature three seagrass systems. This assignment of ecosystems was used. Overhead Index (OI) was trophic levels to the functional groups did not used to identify which ecosystems is more stable differ from the those described in the seagrass and can recover faster after unexpected disturbances model reported in Laguna Alvarado, western [40]. Cycling of matter that regulate the Gulf of Mexico [44], wherein fish and magnitude of flows in the seagrass systems invertebrate groups were placed in the third and was also analysed based on the Finn Cycling second trophic levels. Index (FCI) [40-41]. Trophic transfer efficiency The total living biomass was 1165 tWW (TE) across trophic levels based on the proportion km2 a-1, 1430 tWWkm2 a-1, and 1330 tWW km2 of the organic matter input was summarized a-1 in Seagrass Models for Cagbanilad Bay, the complex food web into a linear food chain Sabitang Laya Island and Nipa Bay, respectively. using the Lindeman trophic analysis [41]. The most dominant group composing the 30% of the total biomass in Cagbanilad Bay, 41% in Results and discussion Sabitang-Laya Island, and 36% in Nipa Bay 1) The input and output parameters seagrass models, respectively, are the seagrasses. Tables 1-3 show the basic parameterization Fish comprised 1.7% to 2.6% of the total biomass results for seagrass models for the three study in the three models. When compared to the sites. The feeding matrices can be shown in smaller scale models for the seagrass models of Supplementary Material 2. The food web models Maqueda Channel, Caramoan Peninsula, the provided the basic and informative descriptions larger scale models developed by by other of seagrass community showing their feeding researchers [42-43] showed almost similar relationships. The three seagrass systems in values in terms of total biomass for primary Maqueda Channel, Caramoan Peninsula are producers. 20 App. Envi. Res. 41(3) (2019): 14-31

Flow to Flow detritus

mort Other Other

5.19 5.19 5.17 3.24 3.26 205.2 248.5 5.48 5.48 6.48 2.95 6.61 1.95 260.3 1.82 140.3 88.96 mort mort 17.45 12.97 2206

------

-- 0.70 ------

------0.25 0.25 0.34 0.31 0.43 0.50 0.75 108.8 436.9 20.89 5.74 0.18 0.25 42.0 206.1 0.20 0.20 0.25 0.27 0.60 0.30 70.04 0.33 0.50 0.38 3.20 0.20 0.82 0.63 0.19 0.68 204.8 0.03 0.25 0.42 101.1 0.24 2.60 0.27 24.52 51.74 13.50 0.44 622.1 1.40 4.46 0.19 339.0 31.67 81.92 0.14 43.85 4.05 0.22 38.81 0.15 217.7 116.1 0.13 0.13 0.16 0.03 129.2 13.58 0.08 39.89

al inlet of Tinago in Minalahos Island) seagrass system model model al inlet of Tinago in Minalahos Island) seagrass system EE P/Q NE OI Resp Predat 0.41 0.41 0.99 0.99 0.20 0.25 0.65 524.6 4.98 0.03 181.9 0.61 0.61 0.61 0.62 0.62 0.67 0.97 0.14 0.30 0.170 0.76 0.79 775.1 1.13 300.0 1.20 0.95 0.79 2.00 0.20 0.58 0.35 0.06 0.25 0.52 285.5 0.44 0.65 0.18 0.29 125.1 0.77 0.16 512.6 0.22 0.77 1314 4.20 -- 43.85 0.25 1030 23.15 180.3 3.34 799.6 2.58 472.6

) -1

Q/B (a

) -1 P/B P/B (a

) -2 5.06 5.06 9.75 39.06 0.95 19.80 19.80 -- -- 65.50 65.50 36.20 4.93 5.01 14.50 25.00 0.95 76.20 76.20 184.1 8.43 30.42 -- -- 44.90 44.90 89.50 0.52 87.50 1.78 2.60 25.60 2.06 13.05 16.30 0.95 4.00 6.86 30.80 3.80 15.00 46.60 2.80 12.50 33.90 0.95 4.45 5.60 33.40 0.95 3.08 22.25 0.95 4.45 16.35 0.95 22.25 0.95 72.10 48.80 8.43 63.30 8.43 -- 8.43 -- -- 15.17 15.17 15.50 67.00 66.30 1.63 192.0 88.30 4.47 12.46 8.42 25.00 0.95 --

(t km

1.00 1.00 3.76 3.76 3.46 3.34 1.00 1.00 1.00 3.09 3.09 3.04 3.02 2.76 2.63 2.34 2.32 2.32 2.27 1.00 1.00 1.00 2.13 2.00 2.00 1.00

Basic inputs and estimated outputs (bold) of Cagbanilad ( Basic inputs and estimated hemprichii Proteroaster nodosus Synapta maculata Cymodocea rotundata ovalis Halodule univervis Tripneustes gratilla Cymodocea serrulata

4 1 2 Syngnathidae 3 Crustaceans Jellyfish 5 6 Omnivorous fish 7 Pelecypods 8 Other benthic feeding fish 9 Other Holothuria 22 Detritus 20 21 Phytoplankton 10 Gastropods 11 Ophiuroids 12 17 18 19 13 Zooplankton 14 Polychaetes 15 16

Group name TL B

Table 1 App. Envi. Res. 41(3) (2019): 14-31 21

Flow to Flow detritus

mort mort Other

5.00 5.00 3.43 274 7.76 7.76 3.65 0.67 0.85 4.78 24.6 7.58 322 2199 5.79 5.79 2.64 182 8.03 8.03 0.40 15.2 mort mort 17.45 13.6 2355

------

-- 0.70 ------

------0.19 0.19 0.24 0.44 321 4.42 0.15 110 0.13 0.13 0.16 0.03 220 6.80 0.08 67.9 0.20 0.20 0.25 0.60 92.5 2.10 0.03 32.4 0.25 0.25 0.34 0.31 0.20 0.43 0.49 0.25 0.74 131 0.64 311 16.0 0.27 468 8.16 0.30 0.49 0.33 5.15 0.20 0.25 0.38 0.83 50.6 0.25 0.25 0.68 147 244 0.27 164 97.3 1.55 585 13.9 2.45 31.0 0.19 97.6 0.22 42.2 205 model rass system

EE P/Q NE OI Resp Predat 0.64 0.64 0.50 0.63 0.37 133 1.79 1.01 169 0.88 0.88 0.20 0.25 0.29 498 3.90 0.55 186 0.58 0.58 0.35 0.44 0.16 1314 39.0 28.0 0.29 852 0.82 0.82 0.18 0.22 -- 663 3.68 0.79 247 0.57 0.57 0.14 0.17 0.78 826 1.01 0.77 323 0.99 0.99 0.30 0.38 1.12 285 2.05 0.01 115 0.58 0.58 0.59 0.59 0.92 0.92 0.10 0.10 0.69 0.69 0.43 0.43 0.95 0.95

)

-1 (a Q/B

) -1 P/B P/B (a

) -2

79.3 79.3 4.45 22.25 32.1 32.1 37.3 3.08 4.45 16.35 22.25 0.95 15.2 15.2 67.0 192.0 26.4 26.4 42.7 1.63 4.47 12.46 25.00 0.95 95.4 95.4 1.78 13.05 59.3 59.3 0.52 83.1 2.60 2.06 0.95 6.86 6.10 6.10 46.7 9.75 31.2 4.93 39.06 5.01 14.50 0.95 25.00 0.95 30.5 0.95 15.7 4.00 43.8 3.80 15.00 2.80 12.50 0.95 5.60 0.95 0.95 79.9 79.9 8.43 -- 69.0 69.0 8.43 -- 67.3 67.3 8.43 38.2 38.2 8.43 -- 36.7 36.7 8.43 -- 19.80 19.80 -- -- 184.1 184.1 30.42 -- 290.0 290.0 8.43 -- (t km

2.33 2.33 2.32 2.32 2.27 2.27 2.13 2.13 2.00 2.00 2.00 2.00 3.04 3.04 3.02 3.02 3.08 3.08 3.75 3.75 3.45 3.34 2.72 2.63 2.34 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

outputs (bold) of Sabitang Laya seag Basic inputs and estimated Synapta maculata Synapta maculata Tripneustes gratilla Tripneustes gratilla Proteroaster nodosus Proteroaster nodosus Cymodocea serrulata Cymodocea serrulata Cymodocea rotundata Cymodocea rotundata Syringidium isoetifolium Syringidium isoetifolium Enhalus acoroides Halophila ovalis Halophila ovalis Halodule univervis 5 Omnivorous fish 6 Pelecypods 1 Syngnathidae 2 Crustaceans 3 Jellyfish 4 7 feeding fish Other benthic 8 Nematodes 9 Other Holothuria 12 15 10 Gastropods 11 Ophiuroids 13 Zooplankton 14 Polychaetes 16 23 Detritus 17 20 21 22 Phytoplankton 18 19 Group name TL B

Table 2 22 App. Envi. Res. 41(3) (2019): 14-31

-- Flow to Flow detritus

mort Other Other

-- 8.43 1037 -- -- 5.52 5.52 2.90 135.47 8.32 8.32 0.11 2.70 4.19 4.19 4.24 208 3.07 3.07 5.36 607.53 3.73 3.73 4.70 438.93 8.15 8.15 0.28 8.19 mort mort 18.53 11.9 2190

------

------0.63 ------

------0.34 0.34 0.43 0.74 202.77 18.47 0.25 95.65 0.20 0.20 0.25 0.60 187.20 0.71 0.03 65.52 0.27 0.27 0.30 0.33 0.20 0.38 0.83 0.25 0.68 122.40 0.27 126.48 12.51 871.76 10.32 0.20 10.41 0.20 48.96 0.22 54.88 305.11 0.13 0.13 0.16 0.03 113.40 11.47 0.08 35.00

em model model em EE P/Q NE OI Resp Predat 0.95 0.95 0.25 0.31 0.49 156.94 9.28 0.47 60.49 0.69 0.69 0.20 0.25 0.64 481.18 3.47 1.54 209.88 0.66 0.66 0.49 0.49 0.99 0.14 0.30 0.17 0.38 0.78 1.12 643.44 310.23 0.87 2.04 0.90 0.02 261.46 125.97 0.99 0.99 0.93 0.93 0.50 0.63 0.37 74.26 2.62 0.18 57.57 0.50 0.50 0.97 0.97 0.19 0.24 0.44 389.00 2.974 0.11 131.32 0.00 0.00 0.84 0.84 0.87 0.20 0.35 0.25 0.44 0.29 0.16 432.54 1313.72 3.76 58.41 0.69 8.59 166.53 712.79 0.61 0.61 0.34 0.76 0.76 0.36 0.18 0.22 -- 728.36 3.41 1.06 284.27 0.44 0.44 0.97

)

-1 (a Q/B

) -1 P/B P/B (a

)

-2 7.3 7.3 9.75 39.06 120 0.52 2.6.00 0.95 123 8.43 -- 184 30.42 -- 30.4 30.4 32.1 4.93 5.01 14.50 25.00 0.95 74.3 74.3 90.5 1.78 15.3 2.06 13.05 4.00 6.86 15.00 0.95 20.4 20.4 65.3 3.80 2.80 12.50 22.25 0.95 0.95 24.8 24.8 8.43 44.2 44.2 4.45 5.60 49.2 49.2 8.43 -- 38.9 38.9 3.08 16.35 32.4 32.4 4.45 22.25 19.9 19.9 -- -- 13.6 13.6 1.63 12.46 0.95 46.9 46.9 4.47 25.00 93.3 93.3 8.43 -- 29.2 29.2 8.43 -- 46.6 46.6 8.43 -- 15.17 15.17 67.0 192.00 113.3 113.3 8.43 --

(t km

3.45 3.45 3.34 3.75 3.75 3.08 3.08 3.04 3.02 2.72 2.63 2.63 2.34 1.00 1.00 2.33 2.33 1.00 1.00 2.32 2.32 1.00 1.00 2.27 2.27 1.00 1.00 1.00 2.13 2.13 2.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Basic inputs and estimated outputs (bold) of Nipa seagrass syst Basic inputs and estimated Proteroaster nodosus Proteroaster nodosus Syringidium isoetifolium Syringidium isoetifolium Thalassia hemprichii Enhalus acoroides Enhalus acoroides Synapta maculata Synapta maculata Tripneustes gratilla Tripneustes gratilla Cymodocea serrulata Cymodocea serrulata Cymodocea rotundata Halophila ovalis Halophila ovalis Halodule univervis

2 Crustaceans 3 Jellyfish 4 1 Syngnathidae 5 Omnivorous fish 6 Pelecypods 7 feeding fish Other benthic 8 Nematodes 9 Other Holothuria 20 10 Gastropods 21 11 Ophiuroids 22 12 23 Phytoplankton 24 Detritus 13 Zooplankton 14 Polychaetes 15 16 17 18 19 Group name TL B

Table 3 App. Envi. Res. 41(3) (2019): 14-31 23

In Cagbanilad Bay seagrass model, the EE 2) Analysis of the trophic flow interactions of jellyfish, pelecypods, and S. maculata have Figures 2-4 depict the flow diagrams constructed high EE values which suggests the important using EwE for the three seagrass ecosystems. role they play in the trophic web and that they Biomass of functional groups are relative to the face high mortality. The EE of size of the circles and are structured along the phytoplankton, detritus, omnivorous fish, and vertical axis based on their trophic level. Lines T. gratilla) are lower compared to most other link prey sources to predators. Color of the lines functional groups, implying that these groups indicates the magnitude of the flow of materials are not fully consumed. The values of EE of the (t km-2 a-1) from prey to predator. predators estimated in the seagrass models ranked Seagrasses, phytoplankton and detritus are within the limits commonly described in the the three main paths in the seagrass ecosystems. literature [23, 43]. In the Sabitang-Laya Island More biomass was moving towards the detrital seagrass model, the EE of pelecypods and group than was moving away from the seagrass Halophila ovalis (paddle weed, spoon grass or systems. This indicates that much of the grass) are high which suggests their production of seagrasses is unconsumed and importance in the food web and high predation proceeds to detritus to be accumulated. The mortality. The EE of detritus, phytoplankton, and flows from phytoplankton and seagrasses E. acoroides are lower compared to most other indicate that grazing food chains is as important functional groups, implying that these groups as the flows from detritus. Benthic groups, are not fully consumed. A comparison with EE including pelecypods and ophiuroids prey upon values of other seagrass ecosystem model, the phytoplankton hence the biomass of such particularly, that by Ortiz and Wolff (2002), group passed up the food web. despite the heterogeneity in terms of biomass of the compartments, the same was concluded in 3) Analysis of the Mixed Trophic Impacts terms of the fate of the production. Furthermore, (MTI) of the functional groups the similarity of the present models in terms of Mixed Trophic Impact (MTI) analyses for the EE of detritus compared with other models the seagrasses system in the three sites (Figures [25, 42] can be explained by almost similar 5-7) simply quantified all the direct and indirect proportion of the detritus in the diet compositions trophic impacts and can also be considered as a of the epifauna. In Nipa Bay seagrass model, sensitivity analysis [37, 46]. In the modelled the EE of E. acoroides, Cymodocea serrrulata seagrass systems, an assumed decrease in the (serrated ribbon seagrass), C. rotundata (smooth biomass of grazers T. gratilla had a positive ribbon seagrass) and omnivorous fish are lower impact on the biomass of seagrasses. On the compared to most other functional groups, other and, a positive effect on the benthic groups implying that these groups are not fully is expected with an assumed decrease in the consumed. The EE of Syngnathidae, pelecypods, biomass of detritus and phytoplankton. ophiuroids, and H. ovalis have high values The MTI matrix in the seagrass system models indicating their food web importance and high indicated that functional groups in Maqueda level of predation mortality. These EEs of the Channel are closely interconnected. This findings functional groups, particularly for the is opposed to Nanwan Bay (Taiwan) [42] wherein invertebrates in the seagrass meadows are large biomasses of macrophytes and detritus comparable even with other ecosystems such as were little affected by changes in other groups the fringing reefs [42]. hence low fraction of flows utilized by the fish community led extremely low TE in the bay. 24 App. Envi. Res. 41(3) (2019): 14-31

Figure 2 Diagram showing the trophic flow interaction in the Cagbanilad (coastal inlet of Tinago in Minalahos Island) seagrass system where the node indicates biomass, curved lines show food connectivity and arch lines showing trophic levels. (All flows are expressed in t km-2 a-1).

Figure 3 Diagram showing the trophic flow interaction in the Sabitang-Laya seagrass system where the node indicates biomass, curved lines show food connectivity and arch lines showing trophic levels. (All flows are expressed in t km-2 a-1).

Figure 4 Diagram showing the trophic flow interaction in the Nipa seagrass system where the node indicates biomass, curved lines show food connectivity and arch lines showing trophic levels. (All flows are expressed in t km-2 a-1).

App. Envi. Res. 41(3) (2019): 14-31 25

Figure 5 Combined direct and indirect trophic impacts of the functional groups in the Cagbanilad (coastal inlet of Tinago in Minalahos Island) seagrass system model. Blue rectangles indicate positive impacts and red rectangles negative impacts.

Figure 6 Combined direct and indirect trophic impacts of the functional groups in the Sabitang-Laya seagrass system model. Black circles indicate positive impacts and white circles negative impacts.

Figure 7 Combined direct and indirect trophic impacts of the functional groups in the Nipa seagrass system model. Black circles indicate positive impacts and white circles negative impacts. 26 App. Envi. Res. 41(3) (2019): 14-31

4) Analysis of the flow network of organic for Nipa Bay was also higher than the mean TE matter and trophic efficiencies values for the bays of Cagbanilad Bay (23.04%) Flows of the seagrass systems of Cagbanilad and Sabitang-Laya Island (23.65%). Thus, in Bay, Sabitang-laya Island and Nipa Bay as two of the three seagrass models (e.g., Sabitang- depicted in the Lindeman spine were organized laya and Nipa Bay), the TE for primary producers by integer trophic levels (TL), in the form of a was higher than for detritus. This finding is Lindeman spine as shown in Supplementary opposed with those found for other systems Material 3. In order to further examine Trophic [45-47] which indicate that detritus is the main Level I, it was separated into detritus (D) and pathway to support the biological communities primary producers (P). It is shown that flows in the ecosystem. were generally low for higher TLs but high for lower TLs (i.e., from TL I to IV). Consumption 5) Flow network of organic matter and by TL II on detritus and the flows from trophic efficiencies in the seagrass systems zooplankton and benthic invertebrates (TL II to Several statistics were calculated in Ecopath IV) were high. to analyse the status of the seagrass ecosystems In Cagbanilad Bay, TL I and TL II had very and to characterize their scale, maturity and high %TST (54.2% and 33.08%, respectively). stability status (see Supplementary Material 4). In Sabitang-Laya Island, the %TST was also The total system throughput (TST) was highest very high (61.19%) followed by TL II (27.87%). in Sabitang-laya Island, 31596 t km-2 a-1, of The same was observed in Nipa bay, wherein which 36.1% of the total flows constitute the %TST was also very high for TL I (58.33%) internal consumption, 19.59% constitute the followed by TL II (29.15%). The observed respiration, and 25.89 constitute the detritus. greater flows occurring from the higher TLs to Total system throughput (TST) was lowest in lower TLs was reported also in other ecosystems Cagbanilad Bay, 27996 t km-2 a-1, of which [25, 42] wherein flows originate from primary 42.53% of the total flows represent the internal producers and detritus and TE drop consumption, 23.35% represent the respiration, significantly from level I to II; and thereafter and 21.45%, the detritus. In contrast, the TST of continued decreasing. The seagrass system the in the current models are higher than the models therefore provided a vivid indication of averages reported in the literature, particularly the sustainability of living aquatic resources in in Nanwan Bay (China) [42] and Pearl River the seagrass ecosystems, which are mainly Delta coastal ecosystem [25]. based on the trophic structure and flows of An index of maturity of an ecosystem is the biomass through species interactions. ratio between total primary production and total Further analysis showed that the primary respiration (TPP/TR). An index value close to production is a limiting factor in Cagbanilad 1.0 indicates that an ecosystem is nearing a Bay seagrass ecosystem based on the TE related “mature” stage; higher than 1 means the to primary production (22.82%) which is higher ecosystem is in the early developmental stage, than the TE related to detritus (22.48%). In and lower than 1 means an ecosystem is under contrast, TE related to detritus in Sabitang-Laya pressure (for example, organic ). Hence, and Nipa (24.06% and 24.49%, respectively) all the three seagrass systems are in early were higher than the TE related to primary developmental stage and the Cagbanilad seagrass producers (23.45% and 24.30%, respectively) appeared to be the most mature system while indicating that detritus is the limiting factor for Sabitang-Laya Island appeared to be the most these ecosystems. Lastly, mean TE (24.34%) immature. The findings support previous report App. Envi. Res. 41(3) (2019): 14-31 27

[48] that majority of aquatic ecosystems have a current study ranges from 76% to 78%, which TPP/TPR ratios between 0.8 and 3.2. are relatively higher compared with the Pearl The intensity of recycling and efficiency of River Delta (China) (67%) [25], which indicates retaining particular matter measured by Finn’s that the latter is more prone to changes brought cycling index (FCI, % of total throughput) by perturbations. showed that the seagrass system found in Cagbanilad Bay was the most highly recycling Conclusion system (FCI = 4.726) and Sabitang-Laya Island The trophic models of the seagrass systems was the least (FCI = 3.790). These FCI values of Cagbanilad Bay, Sabitang-Laya Island and also showed that the positive in the Nipa Bay provide a summary of the knowledge two seagrass systems had contributed to their of the biomass, consumption, production, food stability. In comparison, the FCI in the seagrass web and trophic structure of these ecosystems, systsme are relatively similar with the FCI in and are comparable to other ecosystems [23, Nanwan Bay (3.5) [42]. 42-48] elsewhere in the world. The models The Connectance Index (CI) and System provide tools to quantitatively investigate the Omnivory Index (SOI) indicate the complexity trophic state of the ecosystem by describing of the inner linkage within the ecosystem, how matter and energy propagate through the hence its maturity. Based on the CI and SOI food web. Therefore, it is possible to obtain a values, Cagbanilad Bay seagrass system model more holistic understanding of structure and has the most complex inner linkage compared functioning of the ecosystems. The modelling with the other three seagrass systems. The CI results indicate that the seagrass ecosystems for Cagbanilad Bay (0.252), Sabitang-laya had three main trophic circulation pathways Island (0.28) and Nipa Bay (0.217) are relatively and most of the activities in terms of flow the same with the Pearl River Delta coastal occurred in the lower part of the trophic web. ecosystem (0.235) [25] but lower than Laguna All the attributes of ecosystem maturity and Alvarado in western Gulf of Mexico (0.3) [44]. stability indicate explicitly that the seagrass In contrast, the SOI for the three seagrass systems of Caramoan Peninsula are mature models (0.469, 0.453, 0.449, respectively) in aquatic ecosystems that require peculiar the current study are higher than Pearl River management and conservation strategies. The Delta (0.328) [25] and Laguna Alvarado (0.25) models can be useful tools for policy [44]. This is indicative of the similarity the development and basis for hypothesis to be modelled ecosystems in terms of ecosystem tested in the future. complexity but not in variety in terms of Many functional groups in the trophic model existing food links. of the three seagrass systems are known to be Overhead (Ø, flowbits), a measure of the dependent on seagrass material. The crustaceans, power or ascendancy of a system to recover holothurid S. maculata and the herbivorous fish from stress and the system maturity, showed assimilate material originating from seagrasses, that among the three seagrass systems, the most mainly seagrass [50]. The seagrass stable is the Cagbanilad Bay seagrass systems. material can be incorporated directly by the In contrast, the Sabitang-Laya Island seagrass or omnivores indirectly through system is more predisposed to perturbation- predation and detrivores as detritus. 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