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Bulletin of Marine Science, 75(1): 79–99, 2004

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Bulletin of Marine Science, 75(1): 79–99, 2004 BULLETIN OF MARINE SCIENCE, 75(1): 79–99, 2004 FISH COMMUNITIES OF SUBTROPICAL SEAGRASS MEADOWS AND ASSOCIATED HABITATS IN SHARK BAY, WESTERN AUSTRALIA Michael R. Heithaus ABSTRACT Seagrass habitats support some of the most productive marine communities and pro- vide critical habitat for many fish species. Previous studies have shown that fish com- munities of seagrass meadows are usually more diverse than those of adjacent habitats. However, most studies have been conducted in very shallow waters and generally have used seining methods to collect fish, which tend to select for slower species as well as small species and size classes. Antillean–Z style fish traps were used to study the fish communities of seagrass and associated habitats in both deep and shallow waters of Shark Bay, Western Australia. While more individuals were caught per trap in veg- etated than in unvegetated habitats, the number of species and biomass was influenced by an interaction of depth and seagrass cover. The structure of fish communities was influenced by an interaction among season, seagrass cover, and depth. Unlike previous studies, a small number of species dominated fish trap catches, most notably, striped trumpeters, Pelates sexlineatus Quoy and Gaimard, 1925 and western butterfish, Pen- tapodus vitta Quoy and Gaimard, 1824. The factors that influenced the abundance of common species, including season, depth, and seagrass cover, often interacted and var- ied among species. This study suggests that future research on fish communities of seagrass ecosystems would benefit from using several sampling techniques and consid- ering multiple environmental factors simultaneously. Seagrass meadows are among the most productive ecosystems in the world and pro- vide critical habitat for many species of fish by providing protection from predators as well as abundant food resources (Bell and Pollard, 1989; Connolly 1994a). Seagrass eco- systems are under increasing pressure and many seagrass habitats are being destroyed rapidly (Shepherd et al., 1989). In order to understand and protect these critical habitats, it is important to document the communities supported by undisturbed seagrass ecosys- tems and understand the factors that naturally influence the distribution and abundance of associated species. The seagrass beds of Shark Bay, Western Australia, are not under threat of human destruction, owing largely to Shark Bay’s remote nature, relatively low commercial fishing pressure, and its listing as a United Nations World Heritage area in 1991. Thus, Shark Bay provides an opportunity to investigate the fish communities of seagrass beds in a relatively undisturbed ecosystem. Fish communities in seagrass habitats are usually both more diverse and contain more individuals than adjacent unvegetated areas (Black et al., 1990; Ferrell and Bell, 1991; Connolly, 1994b; Gray et al., 1996), but this pattern is not universal (Hanekom and Baird, 1984). Most studies on fishes in seagrass habitats have been carried out in very shallow waters (e.g., <1.5 m, Ferrell and Bell, 1991; Gray et al., 1996), and although dif- ferences in species composition and abundance have been found between deep and shal- low seagrass beds (Bell et al., 1992; Travers and Potter, 2002), the generality of these results is unclear. In addition, sampling techniques have been limited largely to seining or trawling, which tend to be selective for smaller species and size classes (Ferrell and Bell, 1991; Gray et al., 1996; de Troch et al., 1996), and are likely to be more efficient at catching slow-moving species than large mobile ones (Travers and Potter, 2002). Fish Bulletin of Marine Science 79 © 2004 Rosenstiel School of Marine and Atmospheric Science of the University of Miami 80 BULLETIN OF MARINE SCIENCE, VOL. 75, NO. 1, 2004 traps have been used successfully to sample fish communities in tropical estuaries (e.g., Sheaves, 1992, 1995) and may provide insights into the fish communities of seagrass habitats different from those obtained by seining and trawling methods because they capture larger individuals, are able to sample fast-swimming species, and can readily be used in a variety of water depths. In this study, I used Antillean-Z fish traps to investigate the structure and diversity of fish communities as well as the distribution and abundance of particular fish species in seagrass habitats and associated unvegetated areas of both shallow and deep habitats. The goals of this study were to 1) describe the fish communities of the Eastern Gulf of Shark Bay using fish traps; 2) determine the patterns of species richness and diversity among different habitats and seasons; 3) determine the factors that influence the distri- bution and abundance of common fish species; and 4) investigate seasonal changes in the size distribution of common species. Methods Study Site.—The study was conducted from June–December 1997, March–July 1998, and February–July 1999 in the Eastern Gulf of Shark Bay, Western Australia (~25°45ʹS, 113°44ʹE; Fig. 1). Shark Bay is a large, semi-enclosed bay with extensive shal- low seagrass beds (< 4 m depth), surrounded by deeper waters (embayment planes, 6–15 m). The boundaries between habitats are generally distinct. To minimize edge effects, areas 4–6 m deep were not included in analyses. Shallow habitats are predominantly covered by seagrasses (~85–90% cover; primarily monospecific stands of Amphibolis antarctica Sonder and Ascherson, 1867 and occasionally Posidonia australis Hooker, 1858), but also contain patches of sand. In contrast, deep habitats (generally > 7.5 m) are covered largely by sand or silt with some isolated seagrass patches (~2–10% seagrass cover). The habitats in this study were classified by two factors: depth (shallow, deep) and cover (seagrass, no seagrass). Shark Bay is situated at the boundary between tropical and temperate waters and both warm- and cold-water fish species are present (Hutchins, 1990). Seasonal fluctuations in water temperatures are found in the study site, which correspond to dramatic changes in the abundance of several species of large vertebrates (Heithaus, 2001). During warm months surface water temperatures are generally above 20°C but they drop to a mini- mum of 14°C in the winter months. Due to the mixed species composition of the bay, these seasonal fluctuations in water temperature may influence the abundance of some species. For the purposes of this paper, seasons are defined as “warm” (September–May) or “cold” (June–August), based on both water temperature and the timing of seasonal shifts in the community of large vertebrates present in the bay (see Heithaus, 2001). Field Methods.—Fish were captured with Antillean-Z fish traps. Traps were ~1.1 m long, 0.6 m tall, and 0.6 m wide and had straight, conical entrances that were tapered from ~40 × 25 cm to 25 × 15 cm at the opening into the trap (see Sheaves, 1992 for a detailed description of trap design). Traps were covered with a small (12 mm) square wire mesh or a larger (35 mm) hexagonal mesh. Traps were baited with ~250 g of cut pilchards Sardinops neopilchardus (Steindachner, 1879) placed in a bait capsule hung from the ceiling of the trap. The bait capsules were made of PVC pipe that was capped at both ends and had numerous 10 mm holes to allow water to flow easily through the capsule while preventing bait removal by fish in the trap. HEITHAUS: FISH COMMUNITIES OF A SUBTROPICAL SEAGRASS COMMUNITY 81 Figure 1. A) Shark Bay, Western Australia. The study site was located in the Eastern Gulf and is indicated with an asterisk. B) The study area was divided into eleven sampling zones for fish trap- ping, indicated with polygons. The lightest color represents shallow water (< 2 m at MSLW) and successively darker colors represent waters 2–5 m, 5–7 m, 7–9 m, and > 9 m. Land is black. Up to ten traps were set concurrently from an 11 m catamaran. In most cases, traps were set simultaneously in both deep and shallow habitats to avoid biases caused by tidal or diel movements of fishes. In addition, an equal proportion of small- and large-mesh traps were placed in each habitat to remove potential biases of mesh size on catches (Sheaves, 1995). The location of the initial trap in a habitat was haphazard but further traps were placed along a line, spaced at least 80 m apart (usually over 150 m) to avoid overlap in catch radii, which was generally < 40 m (Sheaves, 1992). Traps were “soaked” for ~2 hrs to maximize catch rate and minimize trap saturation (Sheaves, 1995). When traps were recovered, the fork length (FL) of every fish was measured and a sample of individuals of each species was weighed using an Ohaus electric balance (Model LS2000, 2000 g capacity, 1.0 g accuracy). All individuals were returned to the water alive. For those spe- 82 BULLETIN OF MARINE SCIENCE, VOL. 75, NO. 1, 2004 cies in which many individuals were occasionally caught in a single trap, length-weight relationships (Table 1) were used to determine biomass without weighing all individuals. Sharks were omitted from biomass analyses due to their disproportionately large size. However, inclusion of sharks in biomass estimates does not change general results. Statistical Methods.—Patterns of species composition and abundance within fish communities were described with principal components analysis. To improve the quality of this analysis, only species with more than 90 individuals were included and all data were log (x + 1) transformed prior to analysis (Clarke and Green, 1988). Only principal components with eigenvalues > 1.0 were included in subsequent analyses (Tabachnick and Fidell, 1983). Species were considered an important factor of a principal component if their loading value was > 0.55 or < −0.55 (Tabachnick and Fidell, 1983). The influences of season, depth, and seagrass cover on the number of species and individuals captured per trap, biomass per trap, and catch rates of each of the ten most common species were investigated using a three-way factorial general linear model de- sign with all analyses conducted in JMP IN 4.0.3 (SAS Institute Inc.).
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