Characteristics of megabenthos diversity on the continental margin
This collection of epibenthic megafauna reveals that Australia’s south-western continental margin (∼18° S–35° S) supports a previously unknown high species richness and novelty in several invertebrate taxa (Table 1). For example, 76 species were added to the Decapoda covered in Poore’s (2004) guide to the fauna of southern Australia – a 9.4% increase. This reflects the fact that the region has been rarely explored. The identifiable species had been previously recorded from shallower shelf depths, the Southern Australian coast, or from the Indo–West Pacific.
Many species (60–70% of the total) were rare, being found in just one or two of the 118 samples taken. These fractions are greater than those of some other megafaunal studies in Australian waters, e.g. 30% of species were found only once in 1340 samples taken in an extensive survey on the continental shelf off Queensland (Pitcher et al. 2007) and 56% of fishes on the western slope were taken in one or two trawls (Williams et al. 2001). Our estimate approaches that found in other poorly explored environments, e.g. 76% of sponge species in deep south-eastern canyons were found at single sites (Schlacher et al. 2007). Apparent rarity is a common finding in megafaunal studies, but most studies (this one included) do not include the replicate sampling that would be necessary to distinguish rarity from sampling efficiency or patchiness.
Scales and roles of habitat heterogeneity for biodiversity distribution
At the regional scale of the Australian south-western margin (a survey region of some 1600 km linear distance), the pattern of distribution of epibenthic megafaunal communities was best explained in the analysis by temperature and oxygen, which vary on large spatial scales. Latitude was also a high-level explanatory variable, indicating the influence of some other correlated, but unknown, factor(s). Other covariates, notably seabed type, were also important explanatory variables for community patterns at smaller megahabitat scales (10–100s of km). Among the identified important covariates, temperature and oxygen exist as vertical and horizontal gradients at the regional scale of habitat, and have strong relationships with depth and latitude (e.g.Fig. 2).
The greater explanatory power of physical covariates other than depth and latitude provides greater insights to the processes driving megafaunal distributions. However, the nature of the analytical methods applied here means that we cannot attribute causal relationships to any of the individual covariates we used, even those with large explanatory power. Key mechanistic drivers may be missing from the analysis; they include those related to pressure and food availability (Carney 2005) and, in some locations, pollution (Haedrich et al. 2008). Most of the covariates are correlated, as the physical processes driving them are identical. However, their explanatory power varies: some are more closely linked to the scales at which megafauna vary. For example, while depth and temperature are correlated, temperature varies along the shelf independently of depth. Our goal was not to attribute causation, but to identify scales of variation and habitat heterogeneity that rely on variation in biological data and appropriate physical covariates.
Many of the covariates used here were interpolated from observations made over significant periods of time, years or longer. Due to this and the distribution of samples in space and time, we cannot expect that there would be much difference between adjacent sites. Possibly, this reduced the power of covariates to explain differences between samples, especially at smaller scales. However, megafauna will not respond to the instantaneous values of the covariates, meaning that coincident point estimates of covariates at the time of sampling are unlikely to be informative at small scales. For example, the oxygen concentration at any one time would have little impact on the long-term patterns that can be observed; long-term averages and a measure of variability, such as standard deviation, should be used to compare with faunal distributions. Neither interpolation nor coincident measurements are likely to detect extreme events that are rare and outside the range expected from the interpolated data. This may include some aspects of seasonality where a sporadic annual or decadal event affects the survival or recruitment of fauna.
Isolating the independent influences of individual covariates on species richness is useful to disentangle cross-correlation of covariates, and examine the influences across taxa. Even at the taxonomic resolution of major taxon, seabed type (as measured by the mean and standard deviation of multibeam backscatter) showed strong and intuitive relationships with some major taxa. Thus, higher diversity on hard bottom (higher backscatter) was seen in sponges (sessile species, most of which require stable seabed for anchorage), and molluscs and echinoderms (including many species associated with consolidated and structured bottom types) (Fig. 5A). Richness of Decapoda, the highest of any major taxon, was greatest at intermediate scales of bottom hardness – perhaps indicating that these bottoms comprise a mixture of rocky and sedimentary substrates at mesohabitat or smaller scales (m to km) that appeals to a wide range of species. The Decapoda taken in this survey included diverse families with diverse ecological preferences, ranging from cryptic species living under rocks to species living on exposed, soft-sediment plains.
Covariates that most influenced benthic megafaunal patterns at a regional scale on the Australian south-western margin reflect ocean circulation and water mass structure. The shelf-edge to ∼250–300 m depth is influenced by the Leeuwin Current (Smith et al. 1991; Ridgway & Condie 2004; Waite et al. 2007) which brings warmer, oxygen-poor tropical waters southwards; these waters cool gradually with increasing latitude as they mix with colder waters. The underlying slope is influenced by the northward-flowing, colder, oxygen-rich Leeuwin undercurrent in ∼200–400 m depths (Waite et al. 2007), with mode and Antarctic Intermediate Water below 400 m. Thus, transitions in temperature which appear to drive the separation of continental shelf communities from those of the continental slope, with mean seabed oxygen concentration then influencing community structure on both shelf and slope, are properties of the water masses that bathe the entire south-west margin. Oxygen is consistently high at the shelf edge, but on the shelf there is a shift in oxygen concentration in mid-latitudes (∼30–32° S), with concentration increasing with increasing latitude. In contrast, oxygen concentrations on the slope decrease as a function of depth, but apparently not latitude, as they are lower in the north. This indicates that the environmental covariates of community structure linked to ocean currents are interacting in different ways in different places.
Seabed types (hard and soft terrains) are highly variable in spatial scale. ‘Hard’ (semi-consolidated or rocky) seabed terrains range from extensive, elongate, depth-parallel rocky banks formed by paleo-coastlines and massive plains of shelf-edge coarse carbonate sediments, to scattered patches of rocky outcrop and sub-crop (e.g.Fig. 2C–E, respectively). Large contiguous areas of ‘hard’ terrain may exist at megahabitat scales or larger (∼10–100 km), while patches may exist at only mesohabitat scale (∼10s m–1 km). Despite their distributions and areal extents being only partly mapped on the Australian south-western margin, their collective areas appear to vary when viewed at the provincial or regional scale. Thus, emergent paleo-coastlines were most evident in the north (Ningaloo) and south (∼>31° S), large rocky banks only in the central survey area (Abrolhos), and large areas of coarse sediments most prevalent in the south (Point Hillier to Bald Island). Local-scale aggregations of hard seabed also co-occurred with canyons (Kalbarri, Two Rocks and Perth), and a small pinnacle feature (Albany). These distributions suggest there is considerable regional-scale heterogeneity of habitats defined by sediment properties (Fig. 2F–H) that determine basic niche requirements: consolidated attachment sites for sessile fauna, and sediment classes suited to the needs of mobile and burrowing fauna (e.g.Thouzeau et al. 1991; Roberts & Davis 1996; Bax et al. 1999, Post et al. 2006; Kloser et al. 2007). The distributions of ‘hard’ bottom types thus represent critical elements of habitat heterogeneity nested within the larger scales of other influential covariates.
Using habitat and biodiversity information for conservation management
We have shown that megabenthos diversity along Australia’s south-western margin varies at a variety of spatial scales, and have presented hypotheses that this diversity results from physical processes also acting over a range of spatial and time scales. The diversity results, at least in part, from regional-scale historical processes mixing faunal elements of the Indo-West Pacific and temperate Australia. Mixing of these faunas has been facilitated since the later middle Eocene (38 mya) by the southward-flowing Leeuwin Current that has enabled fauna of tropical origin to enter and survive in South-western Australia and to co-exist with more temperate forms (McGowran et al. 1997). Large-scale properties of this current and associated water masses (temperature and oxygen) had the highest power in explaining the observed provincial-scale patterns in megabenthos communities on the south-western continental margin. Although this does not determine a causal mechanism for faunal heterogeneity, the indications are that the Leeuwin Current and associated water masses play a key role in determining megabenthos community structure at provincial scale.
Samples distinguishing groups 3 and 4 in the Linktree analysis provided information on factors affecting megabenthos patterns at the megahabitat scale. Sites in the two groups are adjacent to one another but were split based on acoustic backscatter (Fig. 3); the taxa differing most in species richness (Table 1) had the strongest response to acoustic backscatter in the GLM analysis (Fig. 5a). Bottom hardness appears to be an important modifier of megabenthos community at the megahabitat scale, but as other physical covariates were not available at a sufficiently fine-enough scale, we have to be cautious of this interpretation.
It is clear from the information derived from the variety of scales used in this study that the scale of observation strongly influences both hypotheses and inferences. The conceptual hierarchical framework we used to capture spatial scales of habitat heterogeneity is very similar to the hierarchical approach used in the developing management of Australia’s marine biodiversity. It is, we believe, essential for describing, understanding, and managing biodiversity and habitat heterogeneity – especially on continental margins.
The Australian government developed bioregional planning as a framework for managing its marine environment (Commonwealth of Australia, 2005; Heap et al. 2005). A key aim is to ensure that the developing National Representative System of Marine Protected Areas (NRSMPA) meets the requirement of comprehensiveness, adequacy and representativeness (the ‘CAR’ principles, ANZECC 1998). An important finding from our study was that the provincial structure of megabenthos in the area of study broadly aligns with the provincial structure based on fishes, which was used to delimit bioregions to meet the management requirement of comprehensiveness. Ensuring that the NRSMPA is represented in each bioregion should provide for comprehensive management of Australia’s marine fauna, or at least for megabenthic invertebrate and fish fauna.
Our study has also highlighted that taxa are differentially distributed at the provincial and megahabitat scales. The distribution patterns of the relatively species-rich decapods, molluscs and echinoderms were each similar to the distribution patterns of all taxa combined. Rarer taxa either did not show the more detailed patterns (corals) or had narrower distributions (ascidians). Sponges, a relatively species-rich taxon, also had a narrow distribution and, similarly to ascidians, had few representatives on the slope. This may also be true of minor taxa not examined. Thus, achieving representative coverage of rarer taxa or taxa with narrow distributions might not be feasible at the same time as achieving adequate representation of the major faunal groups. The narrow distribution of sponges and ascidians in particular shows the importance of adequately representing shelf-edge habitats in the NRSMPA, which despite ease of identification has been difficult to achieve to date (Williams et al. 2009).
The hierarchical scales of heterogeneity of the megabenthos in this area, the differences between taxa, and the high proportion of apparently rare species make it clear that it will be as important to manage the area outside the NRSMPA as to manage the NRSMPA itself. Management will be required at the different scales that correspond to the spatial heterogeneity of continental margin fauna. This will require the development of additional management instruments focused at the spatial scales and heterogeneity that marine-protected areas fail to address.