OCEANOGRAPHIC PROCESSES OF CORAL REEFS: Physical and Biological Links in the Great Barrier Reef - Chapter 12 pot

A Model of the Ecosystem, and Associated Penaeid Prawn Community, in the Far Northern Great Barrier Reef Neil A. Gribble CONTENTS Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Main Characteristics of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Main Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Structure of Basic Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Parameter Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Primary Productivity, Phytoplankton, and Zooplankton . . . . . . . . . . . . . . . . . . . . 195 The Fishery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Balancing the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200 Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 INTRODUCTION The Australian Great Barrier Reef (GBR) stretches 2000 km along the tropical and sub-tropical east coast of the state of Queensland. This complex of lagoons, coral reefs, shoals, and islands is enclosed in a marine national park which has been desig- nated a multi-use world heritage area. Prior to the declaration of the marine park both commercial trawling and line-fishing were carried out in the inner reef lagoon and inter-reef gutters for penaeid prawns, and on the coral reefs themselves for line- caught species, mainly coral trout. There are currently 650 prawn trawlers and over 1000 line-fishing vessels endorsed to work in the park. 12 189 © 2001 by CRC Press LLC The presence of large-scale extractive fisheries inside a designated world her- itage area requires a delicate balance between the economic needs of the fishery and of conservation programs aimed at preserving biodiversity. For management the objective shifts from optimising sustainable yield of the commercially valuable species to a minimisation of the collateral damage to the ecosystem caused by the process of fishing. This may require compromise in the economic returns to the fish- ery in order to safeguard the biodiversity and environment of this unique area. From a stock assessment point of view, the important parameters for models of the fishery shift from maximum sustainable yield (MSY) to considerations of bycatch and the effect of removal of species on the food web of the tropical coral reef ecosys- tem. Opitz (1996) produced an exhaustive review and trophic-based ecosystem model of a tropical coral reef system in the Caribbean (see also Polovina, 1984). No such model exists for the GBR but Poiner et al. (1998) published the results of a 5-year study of the effects of prawn trawling on the far northern GBR. The latter study focussed mainly on the physical impact to the benthos but it also produced cross-shelf surveys of close to 1000 taxa — from seabirds to polychaete worms. The current study combined the Opitz (1996) template for a coral reef ecosystem with the survey results from Poiner et al. (1998) to produce a “mass-balance” trophic- based ecosystem model of the GBR. This new model incorporated both the trawl and line fisheries, and focussed on the dynamics of the penaeid prawn community in the lagoon and inter-reef habitat. Trawl and line-fishing bycatch was specified and mon- itored as were the biomass of seabirds and the endangered sea turtles. The aim was to provide a tool that could give managers an insight into the effects that changes in fish- eries regulation or spatial zoning would have on the ecosystem of the lagoon and inter-reef as a whole, not just on the commercially targeted species. The two major objectives of the modelling exercise were 1. To describe the ecosystem biomass flows in the far northern GBR, focussing on the penaeid prawn trawl grounds 2. To explore the possible impacts of varying the fishing mortality and reduc- ing discarded bycatch on selected species groups and system productivity MAIN CHARACTERISTICS OF THE MODEL This model represents the ecosystem of the inter-reef and inner lagoon on the GBR cross-shelf, far northern GBR, Queensland (Figures 1a and b). Notable features of this area include a large input of discards from the prawn trawl fishery, the seasonal variation in rainfall (the monsoonal “wet”), and the inter-reef–associated hydrogra- phy of the area. As a consequence, this area experiences seasonal variation in input of detritus to the benthic compartment (both natural and from discarded bycatch) and possibly in primary productivity. The model consists of 25 trophic groups, including seabirds, sharks and rays, demersal fish (several groups), penaeid prawns, benthic invertebrates, zooplankton, phytoplankton, discards, and detritus. The penaeid prawn 190 Oceanographic Processes of Coral Reefs © 2001 by CRC Press LLC group was subdivided into the three commercially exploited species and “other prawns.” Similarly the prey/diet of the prawns was divided into reef-associated and lagoon-associated groups. Discards from commercial line-fishing and trawling were included in the model as a second detritus box, and its consumption was appor- tioned among the major scavengers (seabirds, sharks, jacks, and the prawns/ crustaceans). A balanced model was achieved after adjusting the diet composition matrix (for each of the 25 groups), biomass, and consumption/biomass (Q/B) ratios of some groups. The model was implemented using ECOPATH II software from ICLARM (Christensen & Pauly, 1992) using the ECOSYM and ECOSPACE routines for tem- poral and spatial simulations, respectively. MAIN DATA SOURCES The time period represented by the model is 1993 to 1994. Biomass and species com- positions of the target prawns and of discards were obtained during two research trawl cruises in the study area during this period. Biomass of fish and other non-fish taxa was based on parallel fish trawling and benthic dredge samples taken at the time of the prawn surveys (Poiner et al., 1998). Information on diet, consumption, and production (i.e., to derive Q/B and P/B estimates) was estimated from: • The literature on prawn predation from the Gulf of Carpentaria (Brewer et al., 1991; Salini et al., 1990, 1992, and 1998; Haywood et al., 1998) • FISHBASE 99 (Froese & Pauly, 1999) fish database • Previous Ecopath models: (a) the trophic interactions in Caribbean coral reefs (Opitz, 1993 and 1996), and (b) for the shrimp fishery in the south- west Gulf of Mexico (Sherry Manickchand-Heileman, UBC Fisheries Centre, personal communication) All data not derived from the GBR surveys were taken from tropical prawn (shrimp) grounds with similar general characteristics. The “GBRprawn” model deals with the inner lagoon and inter-reef trawl grounds and concentrates on the prawn trawl fishery, rather than attempting a full-scale model of the entire GBR reef ecosys- tem. (Note: The FISHBASE database has over 2000 fish species recorded from Australian tropical reefs. This list does not include invertebrates, which would add several thousand more species to a full GBR reef ecosystem model.) STRUCTURE OF BASIC MODEL The underlying equations for the ecosystem model are based on the “mass balance” concept (see Polovina, 1984), i.e., Consumption ϩ Import ϭ Production ϩ Respiration A Model of the Ecosystem and Associated Penaeid Prawn Community 191 © 2001 by CRC Press LLC or B i (P/B) i EE i ϭ Y i ϩ Α B j (Q/B) i DC ij where B ϭ biomass (i ϭ prey, j ϭ predator) (P/B) i ϭ production/biomass EE i ϭ production retained within the ecosystem (between 0 and 1) Y i ϭ fisheries catch (Q/B j ) ϭ relative food consumption DC ij ϭ fraction of i prey in diet of j predator and where “production” is the sum of “export ϩ mortality due to predation ϩ flow to detritus,” and where “consumption” is the sum of “production ϩ unassimilated food ϩ respiration” (Christensen & Pauly, 1992). The ECOPATH II software uses network analysis of biomass flows in a steady- state (equilibrium) ecosystem expressed as a set of linear functions in a system of simultaneous linear equations. The model is standardised to gram wet weight per square metre and equivalent annual rates of flow (Christensen & Pauly, 1992). ECOSYM and ECOSPACE are modelling tools for representing spatially aggre- gated dynamics of whole ecosystems by a combination of differential equations for biomass dynamics of some of the ecosystem components or “pools.” These are used along with delay-difference age-structured equations for some key populations that have complex trophic ontogenies and selective harvesting of older animals (Walters et al., 1998). The differential equations for aggregate biomass pools are of the form ᎏ d d B t i ᎏ ϭ g i Α j C ji Ϫ Α j C ij ϩ I i Ϫ (M i ϩ F i ϩ e i ) B i where B ϭ biomass C ϭ consumption g i ϭ net growth efficiency I i ϭ biomass immigration rate M i ϭ non-predation mortality/metabolic rate F i ϭ fishing mortality e i ϭ emigration rate while C ij is the consumption rate of pool i biomass by pool j organisms, i.e., the flow from pool i to pool j per unit time. ECOSIM assumes that consumption rates or flows are limited by “risk manage- ment” behaviour of prey and predator at very small space-time scales, such that prey consumption events take place mainly in foraging “arenas” where prey are vulnera- ble to predation through their own requirements for resource acquisition (Walters et al., 1998). Flows may range from strongly prey controlled (bottom-up) to predator/ prey controlled (top-down). 192 Oceanographic Processes of Coral Reefs © 2001 by CRC Press LLC The rate relationship takes the form C ij ϭ ᎏ (v ij ϩ ␯ ij v a i i j j Ј B ϩ i B j a ij B j ) ᎏ where C ϭ consumption B ϭ biomass a ij ϭ rate of effective search for pool type i by predator j v ij ϭ prey behavioural exchange rate parameter 1 v ij Јϭ prey behavioural exchange rate parameter 2 Note: For derivation see Walters et al. (1998). Growth and mortality accounting in the delay-difference framework is structured so that species represented by split pools (juveniles vs. adults) display overall bio- mass dynamics and ecosystem linkages/dependencies similar to the differential equa- tion for aggregate pools. An added complexity is that adult biomass dynamics can depend strongly on recruitment changes caused by changes in trophic circumstances faced by juveniles. Input parameter estimates were derived from the ECOPATH II model. C ij esti- mates were taken as the Q ij estimates from the ECOPATH model to calculate the crit- ical feeding rate parameters, a ij and v ij . Additional growth data for the split pools (juvenile vs. adults if these are specified) needed to be supplied (Walters et al., 1998). PARAMETER DATABASES Fish and non-fish groups were those determined by Opitz (1993 and 1996) for a Carribean Reef coral system using intuitive and multivariate methods of aggregating species into groups based on diet consumption, body size, and lifestyle. Fish species lists were compared between the survey data of Poiner et al. (1998) and those of Opitz (1996) and matching or analogous species assigned to the appropriate “functional” group. Due to a high level of endemism in both the GBR and the Caribbean only 6 species were directly comparable but 27 genera matched, and there was a very good match at the family level. “Large fish” were defined as greater than 30 cm maximum size as described in FISHBASE 99 (Froese & Pauly, 1999). This somewhat arbitrary length was determined heuristically as a natural division of fish sizes in the survey data. Diet (carnivore, omnivore, or herbivore) and lifestyle (schooling or non-school- ing) information was taken from species descriptions in FISHBASE 99 (Froese & Pauly, 1999) and Randall et al. (1990). The two herbivore groups of Opitz (1996) were combined as one in the “GBR prawn” model; survey data (Poiner et al., 1998) showed the biomass in these groups separately was very low in the lagoon and inter-reef. A similar aggregation process was carried out with the non-fish taxa of the GBR to assign them to the grouping of Opitz (1993 and 1996). Cephalopod biomass was a summation of estimates from the benthic dredge and from the fish-trawl sampling data (Poiner et al., 1998). It was considered that each gear sampled a different com- ponent of the cephalopod community and therefore the best estimate of total biomass A Model of the Ecosystem and Associated Penaeid Prawn Community 193 © 2001 by CRC Press LLC was gained by their summation. Echinoderm biomass was determined from the ben- thic dredge samples (Poiner et al., 1998) with crinoids removed, following the logic of Opitz (1993). Crustacean biomass was again a summation of estimates from the benthic dredge and from the fish-trawl sampling (Poiner et al., 1998) but with the prawn biomass excluded. Penaeid prawn biomass was estimated from combined prawn trawl data and dredge data (Poiner et al., 1998), as these devices sample sepa- rate components of the community; i.e., those that “flick” up into the water column and are caught by the trawl gear, and those that remain buried in the substrate but which are taken by the dredge. Biomass estimates for the “Worms and Molluscs” cat- egory came from a combination of the Polychaeta, Sipunculidae, and Mollusca esti- mates from the benthic dredge data (Poiner et al., 1998). “Sessile animal” biomass estimate was a summation of the Porifera, Cnidaria, Bryozoa, and Ascidiacea, esti- mates from the benthic dredge data (Poiner et al., 1998). The animal component of Cnidarian Corals was calculated as 25% of the biomass, with the remaining 75% taken as the algal symbionts (following Opitz, 1993). The symbiont component was added to the benthic producer/autotroph group. This group was made up of seagrass, algae, and the coral algal symbionts. Biomass estimates for the invertebrate component, including benthic pro- ducer/autotrophs, of the ecosystem were made from a combination of benthic dredge and fish trawl bycatch data, however, as only the lagoon and inter-reef were sampled this is a very large underestimate of the biomass if the reef proper were added. Biomass estimates for seabirds and turtles were taken from Opitz (1996) but these were consistent with the information from Poiner et al. (1998), although no spe- cific “catch” rates were quoted in the latter study. In the case of seabirds, little direct predation or harvest was included in the model but the bird colonies do produce chicks, therefore a net emigration (or effective loss of biomass to the system) was included. Turtles are harvested by indigenous communities in northern Queensland, therefore this catch together with the trawl bycatch was included in the “Fleet” fish- ing component of the model. In the absence of hard data these catches could only be approximated. The catch rate of each species in the GBR surveys was reported as gram per hour by Poiner et al. (1998). This was converted to biomass in gram per square metre by dividing the catch rate by the area in meters swept per hour by the sampling gear used (prawn trawl, fish trawl, or benthic dredge). Given the inefficiency and size selectiv- ity of trawl gear, a catchability coefficient (q) of 0.3 to 0.5 was assumed; hence the relative biomass estimates were multiplied by a factor of 3 to give more realistic ini- tial biomass estimates. The dredge data were taken as a reasonable initial estimate, as escapement and size bias of benthos would be low for this type of gear. The biomass estimates were then summed for the species assigned to each group, giving an initial group biomass estimate. In effect this scaled the Caribbean reef ecosystem “template” to that of an Australian GBR system. The diet composition data were taken from the review in Opitz (1996), supple- mented by what was available on FISHBASE 99 (Froese & Pauly, 1999) and in the literature on species of the GBR. Similarly, initial estimates of P/B and Q/B for the functional groups were based on those of Opitz (1996) where local estimates were 194 Oceanographic Processes of Coral Reefs © 2001 by CRC Press LLC unavailable. The Opitz estimates were for an unfished area, therefore the biomass of the “fished” GBR could be expected to be lower (as was the case), which would give the GBR relatively higher P/B and Q/B ratios, particularly for targeted species. The second phase of the specification process was to add groups that were par- ticular to the GBR or that were of particular interest in terms of the effects of fishing on the ecosystem. Initially these were the major commercial species of prawns and the discarded bycatch (detritus/discards) that is generated from prawn trawling. The Ecopath model of the prawn fishery in the southern Gulf of Mexico (Sherry Manickchand-Heileman, UBC Fisheries Centre, personal communication) was used as a general source of estimates for these components of the GBR model. Again local estimates of the biomass of prawn species and discarded bycatch were used where possible (see Poiner et al., 1998). Fate of the discards, as components of scavenger diets or as detritus, was estimated from diet studies (FISHBASE) and Poiner et al. (1998). PRIMARY PRODUCTIVITY, PHYTOPLANKTON, AND ZOOPLANKTON Phytoplankton, micro- and meso-zooplankton abundance, biomass, and produc- tion/consumption estimates for the GBR were taken from Sorikin (1994). Primary productivity estimates (excluding phytoplankton) were taken as an average from var- ious authors including Johnson et al. (1995), Roman et al. (1990), and Klump et al. (1988). THE FISHERY The fishery was divided into two fleets: • The reef line fishery for large reef/inter-reef carnivores, both schooling and non-schooling fish, which was combined with the indigenous harvest of tur- tles (FLEET 1). • The prawn trawl fishery for penaeid prawns (FLEET 2), which produces the highest proportion of discarded bycatch. Poiner et al. (1998) estimated a ratio of 8:1 to 12:1 by weight of bycatch to retained catch. Harvest rates for the prawn trawl fishery were taken from Gribble and Robertson (1998). Both legal and illegal fishing were included in the biomass estimates but these were spread over the total area modelled. Gribble and Robertson (1998) found that within the GBR study area small areas or regions could be heavily trawled (e.g., parts of the inshore lagoon), while the majority received relatively little or no trawling. Therefore it was found to be necessary to scale this harvest biomass slightly to bal- ance the model. Similarly the trawl bycatch biomass had to be scaled. The majority of the bycatch or detritus/discards was “trash” fish consisting of small bottom omni- vores and herbivores (Figure 2). A small biomass of adult turtles was taken as trawl A Model of the Ecosystem and Associated Penaeid Prawn Community 195 © 2001 by CRC Press LLC bycatch, which required adjusting its P/B ratio (i.e., analogous to total mortality or Z) upward. Effectively the fishery was another consumer in the model and its “diet” was the catch composition. Harvest rates for the line/indigenous fishery were roughly estimated from the QFMA QFISH compulsory catch and effort logbook database. The major difficulty was to determine the biomass in g m 2 when there was no way of calculating a “swept area” for either recorded line-fishing or non-recorded indigenous/recreational fishing methods. The estimates in the model were adjusted to balance the biomass flows but should be considered as intuitive rather than precise. BALANCING THE MODEL First attempts at running the model gave values of EE (ecotrophic efficiency) greater than 1 for almost all the groups, i.e., more biomass was utilised within the ecosystem than actually existed. This presented a problem in balancing the model since there was very little flexibility for adjusting the biomass matrix (determined from survey). There was scope, however, to increase the biomass of the mobile carnivores, as pre- sumably they would have used the reef as a refugia, hence biasing the lagoon and inter-reef fish trawl catch downward significantly. The benthic producer/autotrophs would also have been underestimated because of their occurrence on the reef proper outside the range of the inter-reef benthic dredge. It also appeared that the estimate of discards was too high. This was adjusted downward to “spread” the discards over the total area modelled and to scale the biomass of discards (determined from prawn trawl data) in line with the biomass of its component species (determined from fish trawl data). Poiner et al. (1998) noted that the prawn trawl was more efficient at har- vesting the smaller bottom dwelling fish than the fish trawl. The parameter estimates of Q/B and P/B were based on Opitz (1996) and were low for some of the fished species. The Opitz estimates, however, were from an unfished reef; therefore, to com- pensate, the estimates for these species were adjusted upward by 50%. Most fine-tuning was carried out in the diets of the various trophic groups, where there was a degree of flexibility. A trophic group was an amalgam of species with dif- ferent dietary preferences, therefore the group as a whole had a reasonably gener- alised diet. Opitz (1996) allowed for this, for example, by defining herbivores as having greater than 50% plant material in their diet. Insufficient detritus in the model remained a problem after all other trophic groups were balanced. This was tackled in two ways: 1. The extra detritus needed was considered as an import to the lagoon and inter-reef system from the land and from the reef proper. 2. The autotroph biomass component of the ecosystem was increased to pro- vide the required detritus, which could be justified as coming from the pri- marily autotrophic reef proper. Allied with this problem was the lack of prey biomass for the biomass of fish preda- tors in the model. To compensate the biomass of fish herbivores was increased in line 196 Oceanographic Processes of Coral Reefs © 2001 by CRC Press LLC with the increase in autotrophs (option 2 above). As with mobile carnivores, the reef- associated herbivores would have been under-represented in lagoon and inter-reef fish trawls; therefore the relative increase was logical. In both cases, after adjustment, re-scaling, and diet fine-tuning it was possible to achieve a preliminary balanced model. A small import of detritus from the land was kept in the model to allow for output from coastal mangrove systems. Finally, minor increases to the P/B estimates for echinoderms, benthic mol- luscs/worms, and decomposer/microfauna were necessary to bring their respective gross efficiency or production/consumption ratios (see Table 1) down to below the recommended 0.3 (V. Christensen, UBC Fisheries Centre, personal communication). This required further fine-tuning of the diet matrix to re-balance the system. Lack of data for some of the species was a problem. Since the discards consist of species of no economic importance, published information on diet in particular was sparse. Also, more precise estimates of the quantity of discards and proportion consumed by each scavenger group were needed. SIMULATIONS A fine-tuning process was required to re-balance the model as published by Opitz (1996), due in part to the slight differences in versions of ECOPATH II software used by the respective authors. All changes made were within the tolerances suggested by Opitz (1996) as appropriate to the collated data she used. More realistic values from the GBR were substituted and the model re-balanced. Again the changes made were kept within reasonable limits. The biomass estimates from the surveys (Poiner et al., 1998) were robust with only increases between factors of 1.5 and 4 needed, with the special exception of the biomass of autotrophs and fish herbivores, which were increased by a factor of 100 and 8, respectively (see the section “Balancing the Model” for explanation). underlying assumptions of the model and a different set of assumptions may also pro- duce a balanced model. Therefore the “GBRprawn” model should be viewed as a “virtual” lagoon and inter-reef ecosystem which captures the major biomass dynam- ics and flows of the “real,” much more complex system. “Reality” checks were nec- essary, comparing the behaviour of the simulations to that observed independently through logbooks or fishermen’s anecdotal experience. That is, the results had to be kept biologically reasonable. As noted earlier, the spatial nature of the GBR habitat/ecosystem was in part incorporated in the diet matrix, i.e., diet composition of inter-reef species vs. that of species found in the inshore reef lagoon. This spatial component to the model was explored further using the ECOSPACE simulation routine. The dynamic effects of the prawn fishery were explored in ECOSYM simulations (Walters et al., 1998). Both these simulation routines used the balanced ECOPATH II “GBRprawn” model as a model. Both transient and long-term effects of trawling on the prawn stocks were A Model of the Ecosystem and Associated Penaeid Prawn Community 197 © 2001 by CRC Press LLC These adjustments to biomass, Q/B, P/B, and diet composition represent the starting point. Tables 1 and 2 present the input parameters for the “GBR prawn” simulated with the fishing scenarios and results presented in Figures 5 and 6. These simulations were used primarily to “reality check” the basic ecosystem model, as the historic behaviour of the targeted stocks is the best documented, i.e., through com- pulsory catch and effort logbooks. Fisheries Critical Issues Group, where a 5% reduction in effort per year was applied specific reduction in fishing area was applied nor were Marine Representative Areas (MPAs) introduced, although this is possible in the model. Table 3 presents the changes in biomass and commercial catch described by the scenario, with before and magnitude of change). 198 Oceanographic Processes of Coral Reefs TABLE 1 Basic Parameters for Ecopath Ecosystem Model of the Far Northern GBR Inter-Reef and Lagoon Group Trophic Biomass Prod/Biom Cons/Biom Ecotrophic No. Group Name Level (t/km 2 ) (/year) (/year) Prod/Cons Efficiency 1 Cephalopods 3.50 0.328 4.590 17.550 0.262 0.921 2 Large groupers 3.50 0.035 0.370 2.300 0.161 0.906 3 Scombrids/jacks 3.50 2.024 0.720 8.900 0.081 0.681 4 Seabirds 3.40 0.015 5.400 80.000 0.068 0.904 5 Large sharks/rays 3.30 0.557 0.240 4.900 0.049 0.793 6 Small schooling fish 3.20 3.122 2.250 20.050 0.112 0.973 7 Large fish carnivores 3.10 1.780 0.960 10.960 0.088 0.946 8 Large schooling fish 3.10 0.600 1.246 12.700 0.098 0.912 9 P. longistylus 2.90 0.064 7.570 37.900 0.200 0.953 10 Other prawns 2.80 0.201 1.100 20.000 0.055 0.992 11 P. esculentus 2.80 0.177 7.570 37.900 0.200 0.825 12 Small fish omnivores 2.70 2.226 2.355 12.800 0.184 0.917 13 Sea turtles (large) 2.50 0.007 0.900 3.500 0.257 0.952 14 Crustaceans 2.50 2.741 3.100 20.000 0.155 0.987 15 M. endeavouri 2.50 0.142 7.570 37.900 0.200 0.873 16 Ectiinoderms 2.40 8.404 1.500 6.000 0.250 0.842 17 Benthic molluscs/worms 2.30 10.972 2.900 10.000 0.290 0.992 18 Zooplankton 2.20 3.216 40.000 165.000 0.242 0.716 19 Sessile animals 2.00 30.950 0.800 12.000 0.067 0.940 20 Fish herbivore 2.00 7.116 2.730 37.450 0.073 0.856 21 Decomposer/microfauna 2.00 6.000 120.000 400.000 0.300 0.197 22 Phytoplankton 1.00 7.515 70.000 0.855 23 Benthic autotrophs 1.00 175.109 13.250 0.156 24 Detritus/discards 1.00 3.836 0.966 25 Detritus 1.00 40.000 0.683 biomass utilised within the ecosystem. © 2001 by CRC Press LLC The final set of simulations follows the scenario suggested by the GBRMPA Note: “Prod” ϭ production, “Cons” ϭ consumption, “Ecotrophic Efficiency” ϭ the proportion of the after estimates plus the ratio of end-to-start biomass and catch (i.e., direction and until the effort reached 50% of current 1997 levels (Figure 7 and Animation 1). No [...]... fishing increased farther offshore into the inter -reef habitat The line fishery fleet was restricted to the reef- shoal and inter -reef habitats Again it was made slightly more “costly” to line-fish in the offshore sections of these habitats rather than in the more accessible inshore edge of the reef shoal and inter -reef The rationale for these increasing costs was the increased fuel required, loss of fishing... LLC 206 Oceanographic Processes of Coral Reefs FIGURE 1a Map of Queensland showing the far northern GBR study area Dotted areas represent shoals and submerged reefs a FIGURE 1b Simulated study area used for ECOSPACE spatial simulations of the effects of trawling on the GBR ecosystem (Land/islands area in black, blue ϭ inner lagoon, light-green ϭ reef/ shoal, med-green ϭ inter -reef, dark-green ϭ offshore... i.e., the model was made spatially explicit Fishing was also assigned to habitat types but was further restricted by mapping the “costs” of fishing in the different habitats Penaeus esculentus was assigned to the inshore lagoon, P longistylus to the inter -reef habitat, and M endeavouri straddled both habitats The trawl fleet could fish in both the inshore lagoon and the inter -reef but the cost of fishing... trawlers and line-fishers in the far northern GBR (Gribble & Robertson, 1998; Poiner et al., 1998) Spatial simulations of the scenario above, with a reduction followed by a reintroduction of trawling, showed that the spatial distribution P longistylus did ameliorate the effect of trawling seen in the ECOSYM dynamic simulation (Figure 5) The difficulty of trawling in the outer region of the GBR cross-shelf... higher “cost” of trawling in this region) means that a proportion of the red-spot king prawn population is not vulnerable to trawling This is effectively a de facto marine protected area (MPA) for this species Similarly, the sea-turtle biomass rose significantly during the initial years of the simulation because of the offshore refugia, hence the reduction in trawling had less of an impact The trajectory... associated with the reef and inter -reef [see Poiner et al., 1998]) but not for the logbook data on P longistylus which showed no relative decrease The drop was almost certainly caused by the spatial distribution of this species (or lack of it in the ECOSYM simulations), which was explored further using ECOSPACE Large parts of the reef- shoal habitat are normally not available to trawling due to the physical. .. gear in the rougher terrain, and an increased risk of boat damage in the mostly uncharted offshore shoal -reef zone The offshore lagoon habitat was not fished in this simulation because of its exposed position, very rough bottom (extensive plate coral) , and to provide a refugia for turtles and seabirds around nestsite islands and shoals This scenario broadly matched the known fishing behaviour of trawlers... 1.000 A Model of the Ecosystem and Associated Penaeid Prawn Community TABLE 2 Diet for Each Trophic Grouping in the Ecopath Ecosystem Model of the Far Northern GBR Inter -Reef and Lagoon 1.000 199 © 2001 by CRC Press LLC 200 Oceanographic Processes of Coral Reefs TABLE 3 Results from “GBRprawn” Simulation of a 5% Reduction in Prawn-Trawl Effort per Year Applied until the Effort Reached 50% of Current 1997... analysis of the mixed trophic impacts in the far northern GBR lagoon and inter -reef ecosystem © 2001 by CRC Press LLC A Model of the Ecosystem and Associated Penaeid Prawn Community 207 FIGURE 5 ECOSYM dynamic simulation of the transient effect of varying trawl effort on the biomass of the three major commercial prawn species FIGURE 6 ECOSYM dynamic simulation of a 100-year time-series effect on the three... rapid initial adjustment of the ECOPATH biomass estimates for the spatial distribution, then relatively smaller impact of the change of trawl effort, due to the presence of offshore spatial refugia ANIMATION 1 ECOSPACE simulation of the effect of spatially explicit habitat (see Figure 1b) and areas fished on the dynamic simulation of the scenario of a 5% drop in trawl effort per year until 50% of the . to line-fish in the offshore sections of these habitats rather than in the more accessible inshore edge of the reef shoal and inter -reef. The rationale for these increasing costs was the increased. inter -reef but the cost of fishing increased farther offshore into the inter -reef habitat. The line fishery fleet was restricted to the reef- shoal and inter -reef habitats. Again it was made slightly. and line-fishing were carried out in the inner reef lagoon and inter -reef gutters for penaeid prawns, and on the coral reefs themselves for line- caught species, mainly coral trout. There are currently