36 Rock

Lobster

Habitat

Assessment

Figure 20. Nine Mile Reef video survey sites (see Table 4 for biota codes).

a. NMR01a low profile reef, sessile invertebrates. d. NMR03a low profile reef, sessile invertebrates.

b. NMR02a low profile reef, sessile invertebrates. e. NMR05a high profile reef, sessile invertebrates.

c. NMR03a low profile reef, sessile invertebrates. f. NMR06a low profile reef, sessile invertebrates.

Rock Lobster Habitat Assessment 37

g. NMR06a low profile reef, sessile invertebrates. i. NMR09a low profile reef, sessile invertebrates.

h. NMR08a High profile reef, sessile j. NMR09a low profile reef. invertebrates.

Figure 21. Nine Mile Reef video still images.

Rock Lobster Habitat Assessment 38

Rock

Lobster

Habitat

Assessment Figure 22. Torquay and Ocean Grove (western area) video survey sites (see Table 4 for biota codes). 39

40 Rock

Lobster

Habitat

Assessment

Figure 23. Torquay and Ocean Grove (eastern area) video survey sites (see Table 4 for biota codes).

a. OGT05a low profile reef, sessile invertebrates. d. OGT12a patchy low profile reef, sessile invertebrates / E. radiata

b. OGT06a patchy low profile reef. e. OGT16a low profile reef, E. radiata / Cystophora spp.

c. OGT11a high profile reef, E. radiata. F. OGT17a sediment, A. antarctica.

Rock Lobster Habitat Assessment 41

g. OGT18a patchy low profile reef, Cystophora j. OGT24a patchy low profile reef, sessile spp. invertebrates (Butterfly perch).

h. OGT22a low profile reef, E. radiata / Cystophora k. OGT27a patchy low profile reef ‐ cobble. spp.

i. OGT23a low profile reef, E. radiata. l. OGT30a patchy low profile reef, E. radiata.

Rock Lobster Habitat Assessment 42

m. OGT32a low profile reef, Cystophora spp. p. OGT37a patchy low profile reef, E. radiata / Cystophora spp.

n. OGT33a low profile reef, Cystophora spp. / E. q. OGT39a low profile reef, E. radiata. radiata.

o. OGT35a low profile reef, E. radiata / Cystophora r. OGT39a low profile reef, E. radiata. spp. / Sargassum spp.

Figure 24. Ocean Grove‐Torquay video still images.

Rock Lobster Habitat Assessment 43

approximately 48 m and was often the dominant Summary of Video Observations species. Cystophora spp. was observed up to a The depth distribution of video sites at the rock depth of approximately 44 m typically growing lobster fixed sites is summarised in Figure 25. with E. radiata. A change from the dominant There was some overlap between the depths large brown macroalgae (kelps) to sessile across the fixed sites, but they broadly fell into invertebrates occurred at the 60–80 m depth the following three depth groups: range (Figure 28). This was highlighted by the change from E. radiata dominance at Big Reef to • shallow (<20 m): Warrnambool West and sessile invertebrates at Nine Mile Reef (Figure Warrnambool South 27). Durvillaea potatorum was observed in the • intermediate (21–60 m): Discovery Bay, inshore region up to a depth of approximately Portland, Port Fairy West, Warrnambool 14 m. East, Big Reef and Nine Mile Reef and Ocean Grove‐Torquay • deep (61–120 m) Discovery Bay Deep and Port Fairy Deep. While Portland, Port Fairy West, Warrnambool East and Ocean Grove‐Torquay were predominantly at intermediate depths, they represented a transition from the shallow to intermediate depth group. Nine Mile Reef was at the transition from the intermediate to deep depth group. Dominant substratum types across the fixed sites did not appear to be related to depth (Figure 26). Low profile reef was the most common substratum type and dominated most of the video sites. Warrnambool West was the exception to this, and the only site with predominantly high profile reef. Discovery Bay Deep had a more even spread of substratum types. Low profile patchy/cobble reef dominated at Port Fairy Deep and was also common at the Ocean Grove–Torquay site. The rock lobster fixed sites were typically dominated by a single dominant biota or canopy species and this reflected the depth group of each site (Figure 27). Portland, Port Fairy West and Ocean Grove‐Torquay had the greatest range of dominant biota types. The deepest sites at Discovery Bay Deep, Port Fairy Deep and Nine Mile Reef were entirely dominated by sessile invertebrates. Ecklonia radiata was the dominant species at the majority of the other sites. comosa on its own or growing with E. radiata was an important component of the biota at Portland, Warrnambool, Warrnambool West, Port Fairy West and Ocean Grove–Torquay. The mean percentage cover of dominant biota or canopy species showed a depth zonation across the sites (Figure 28). Phyllospora comosa was observed up to a depth of approximately 29 m and was typically growing with E. radiata. Ecklonia radiata was observed up to depth of

Rock Lobster Habitat Assessment 44

0–20 m 21–40 m 41–60 m 61–80 m 81–100 m 101–120 m

100

90

80 70

60

50 40

30

20 Percentage of video sites 10

0 West Deep Portland Big Reef East West Port Fairy Port Fairy Port South Deep Torquay Warrnambool Warrnambool Warrnambool Ocean Grove- Nine MileReef Discovery Bay Discovery Bay Discovery

Rock lobster fixed site

Figure 25. Depth distribution of video sites (quadrats) at rock lobster fixed sites.

High Profile Reef Low Profile Reef Low Profile Reef - Patchy/Cobble Sediment

100 90

80 70

60

50 40

30

Percentage of video sites 20

10 0 West Deep Portland Big Reef East West Port Fairy Port Fairy Port South Deep Torquay Warrnambool Warrnambool Warrnambool Ocean Grove- Nine Mile Reef Discovery Bay Discovery Bay Discovery

Rock lobster fixed site

Figure 26. Substratum types at video drops (quadrats) at rock lobster fixed sites.

Rock Lobster Habitat Assessment 45

E. radiata E. radiata & P. comosa P. comosa E. radiata & Sessile invertebrates Sessile invertebrates Cystophora spp.

100 90 80 70 60 50 40 30 20 Percentage of video sites video of Percentage 10 0 West Deep Portland Big Reef East West Port Fairy Port Fairy Port South Deep Torquay Warrnambool Warrnambool Warrnambool Ocean Grove- Nine Mile Reef Mile Nine Discovery Bay Discovery Bay Discovery Rock lobster fixed site

Figure 27. Dominant canopy species on video transects at rock lobster fixed sites.

E. radiata P. comosa D. potatorum Cystophora spp. Sessile invertebrates

80

70

60

50

40

30

Mean Percentage Cover 20

10

0 0–20 21–40 41–60 61–80 81–100 101–120 Depth range (m)

Figure 28. Depth zonation and mean percentage cover of dominant canopy species in video quadrats.

Rock Lobster Habitat Assessment 46

Hydro‐acoustic Survey – Warrnambool West The video surveys of the Warrnambool West fixed site showed that it was predominantly high‐profile reef (Figure 26) and this site was selected for the hydro‐acoustic survey. The sidescan sonar data mosaic of the survey area within the Warrnambool West fixed site overlayed with single‐beam sounder and video data is shown in Figure 29. The seabed habitat classification mapping from the sidescan sonar data is shown in Figure 30. Standardised catch data from the fixed site for 2002–07 is overlayed on the habitat classification in Figure 30. This shows a pattern of fishing effort clustered around the boundary of the high profile reef. Figure 30 does not show the location of pots with zero catches as these were not included in the rock lobster fixed site database. The boundary between the high profile reef and sediment at the eastern end of the mapping area is highlighted in Figure 31. The high profile reef video site at the centre of Figure 31 is site WW02a (Figure 12a).

Rock Lobster Habitat Assessment 47 48 Rock

Lobster

Habitat

Assessment

Figure 29. Sidescan sonar, single‐beam sounder and video data at Warrnambool West rock lobster monitoring area.

Rock

Lobster

Habitat

Figure 30. Habitat classification from sidescan sonar at Warrnambool West fixed site overlayed with standardised rock lobster catches 2002–07. Assessment

49 50 Rock

Lobster

Habitat

Assessment

Figure 31. Sidescan sonar data showing reef detail at Warrnambool West overlayed with standardised rock lobster catches 2002–07

Statistical Analysis Linking habitat and CPUE data The bubble plot overlaying mean cpue values on Catch data the ordination of all habitat parameters also The abundance of rock lobster as measured by showed a correspondence with the three main cpue differed between sites and between years. depth groups. The shallower sites had lower There was a general decline in cpue values over cpue values, and the intermediate and deeper the time period investigated at all sites except sites had higher cpue values, although there was for Warrnambool West and Torquay. While the only catch data from one of the deeper sites i.e. Warrnambool West site showed a general Nine Mile Reef (Figure 36). decline in cpue for the years 2002–06, the 2007 data indicated that the relative abundance of Examination of the other habitat parameters in rock lobster had returned to 2002 levels. In the form of bubble plots suggested that, apart Torquay, cpue values increased over the time from depth, there were seven variables that period, with the highest catch rates recorded in looked likely to be important in contributing to 2006. the observed pattern in the nMDS (Figure 34). These were percent cover of continuous rocky Catch per unit effort was generally higher at the reef (Figure 37), percent cover of high profile western (Discovery Bay sites) and eastern (Big reef (Figure 38), percent cover of understorey Reef, Nine Mile Reef, Torquay) sites, and lower canopy (Figure 39), percent cover of E. radiata in the central sites. The Ocean Grove site did not (Figure 40), percent cover of P. comosa (Figure fit with this pattern and cpue values recorded 41), percent cover of mixed red from this site were consistently low. It should be understorey (Figure 42) and percent cover of noted that the Ocean Grove and Torquay fixed sessile invertebrates (Figure 43). sites were sampled at a different time of year to the other sites (i.e. August versus February). The sites that were at intermediate or deep depths and had higher cpue values also had a Habitat data lower proportion of continuous rocky reef, and a The dendrogram (Figure 32) showed that there lower proportion of that reef was high profile was a high degree of similarity between the reef (Figure 37, Figure 38). Ecklonia radiata and P. habitats at all sites. The deeper sites (Nine Mile comosa were absent at the deep sites and very Reef, Discovery Bay Deep and Port Fairy Deep) little P. comosa was present at the intermediate were separated from the remainder of the sites, sites (Figures 40 and 41). Similarly there was less although these remaining sites could also be of an understorey at the deeper sites (Figure 39), separated into three groups at approximately while there was a greater cover of mixed red 75% similarity. The nMDS also separated the algae in the intermediate and deep sites (Figure sites into three main groups (Figure 33). 42) and more sessile invertebrates (Figure 43). An nMDS analysis using only these seven The separation of the video observations into variables provided the same relative positioning Torquay and Ocean Grove was based on a of the sites on an ordination (Stress 0.09) and is boundary running directly south from Bancoora not shown here as it looked much the same as Beach. Figure 33. Both the cluster analysis and the nMDS Correlation coefficients are shown in Table 6. separated the sites into three main groups based None of the habitat parameters consistently on their habitats and these groups corresponded correlated with cpue values, however there were reasonably well to the average depths of the a number of habitat parameters that were video drops (Figure 34). These groups correlated with cpue in more than one year. corresponded with the overall depth groups of While there were a number of parameters that shallow depths of 0–20 m (i.e. Portland, were correlated with cpue in two out of the six Warrnambool West, Warrnambool South and years (i.e. patchy reef, ledges and overhangs, Port Fairy West), intermediate depths of 21–40 upper storey canopy, and the understorey m (i.e. Discovery Bay, Warrnambool East, Big ), the analysis here focused on the Reef, Torquay and Ocean Grove) and deeper habitat parameters that had significant depths >60 m (Nine Mile Reef, Port Fairy Deep correlations with cpue in three out of the six and Discovery Bay Deep) (Figures 25 and 34). years as this gave more confidence in these Fixed sites that were close together relationships. geographically (Figure 1) did not appear to have more similar habitat (Figure 35).

Rock Lobster Habitat Assessment 51

Depth was significantly positively correlated Phyllospora comosa was significantly negatively with cpue values in three out of the six years correlated with cpue in three years and the and the percent cover of continuous rocky reef percentage of red algae in the understorey and on the transect was significantly negatively the percent cover of sessile invertebrates were correlated with cpue in the same years (Table 6). both significantly positively correlated with The percentage of rubble recorded from the cpue in three of the years. quadrats was significantly correlated with catch in three out of six years, but in both 2003 and 2004 there was an influential outlier and no evidence of a relationship without this outlier.

Big Reef Ocean Grove Ocean Portland West Warrnambool Torquay Discovery Bay Port Fairy West Fairy Port Nine MileReef Deep Bay Discovery Deep Fairy Port Warrnambool Warrnambool East

Figure 32. Dendrogram of habitat parameters from video observations at fixed sites using group average clustering from Bray Curtis similarities. The separation of sites into three groups at 75% similarity is indicated by the dotted line. The separation of the Torquay and Ocean Grove sites is based on a boundary running directly south from Bancoora Beach.

Rock Lobster Habitat Assessment 52

Figure 33. MDS ordination of the video data at rock lobster fixed sites based on untransformed data and Bray Curtis similarities

Rock Lobster Habitat Assessment 53

Figure 34. MDS ordination of the video sites with depth overlayed as a bubble plot. The bigger the circle the greater the depth.

Figure 35. MDS ordination of the video sites with longitude overlayed as a bubble plot. The bigger the circle the further east the site is.

Figure 36. MDS ordination of video sites with mean annual cpue (2002–07) overlayed as a bubble plot. The larger the circle the greater the cpue. No catch data was available for Port Fairy (Warrnambool) Deep or Discovery Bay Deep. Torquay is the pooled mean cpue for Ocean Grove and Torquay.

Rock Lobster Habitat Assessment 54

Figure 37. MDS ordination with continuous reef overlayed as a bubble plot. The bigger the circle the higher % cover of continuous reef along video transects.

Figure 38. MDS ordination with the proportion of high profile reef in video transects overlayed as a bubble plot.

Figure 39. MDS ordination of video monitoring sites with percentage cover of understorey canopy recorded from the quadrats overlayed in a bubble plot.

Rock Lobster Habitat Assessment 55

Figure 40. MDS ordination of video monitoring sites with percentage cover of E. radiata recorded from quadrats overlayed in a bubble plot.

Figure 41. MDS ordination with percentage cover of P. comosa recorded from quadrats overlayed in a bubble plot.

Figure 42. MDS ordination with percentage cover of mixed red algae understorey recorded from quadrats overlayed in a bubble plot.

Rock Lobster Habitat Assessment 56

Figure 43. MDS ordination of video monitoring sites with percentage cover of sessile invertebrates recorded from quadrats overlayed in a bubble plot.

Rock Lobster Habitat Assessment 57

Table 6. Pearson Correlation Matrix for cpue in each year from 2002–07 versus habitat variables (arcsin transform of the square root of the variable).**P<0.05, *0.05

Variables 2002 2003 2004 2005 2006 2007 Depth 0.548 0.469 0.829** 0.616* 0.442 0.606* Longitude ‐0.185 0.31 0.127 0.451 0.487 0.498 % Rocky reef ‐0.16 ‐0.223 ‐0.691** ‐0.689** ‐0.354 ‐0.779** % Patchy reef 0.246 0.237 0.683** 0.591 0.247 0.771** % Sand ‐0.211 0.053 0.344 0.658* 0.512 0.244 % Low profile reef ‐0.104 ‐0.031 0.221 0.396 0.501 0.271 % High profile reef 0.247 0.074 ‐0.194 ‐0.458 ‐0.565 ‐0.262 % Cracks / crevices 0.249 ‐0.486 ‐0.141 ‐0.027 0.013 0.184 % Ledges ‐ overhangs 0.757** 0.578 0.675** 0.285 0.032 0.197 % Conglomerate rock ‐0.242 ‐0.324 ‐0.061 0.492 0.718** 0.354 % Boulders ‐0.07 ‐0.083 ‐0.181 ‐0.261 ‐0.223 ‐0.532 % Cobble 0.132 0.218 0.572 0.584 0.618* 0.385 % Rubble 0.082 0.737** 0.772** 0.751** 0.526 0.521 % Upperstorey canopy ‐0.266 ‐0.894** ‐0.813** ‐0.493 ‐0.141 ‐0.546 % Understorey canopy ‐0.054 ‐0.309 ‐0.446 ‐0.435 ‐0.609* ‐0.336 % Encrusting coralline ‐0.003 ‐0.164 ‐0.466 ‐0.526 ‐0.159 ‐0.075 % E. radiata ‐0.022 ‐0.974** ‐0.564 ‐0.25 ‐0.024 ‐0.17 % P. comosa ‐0.482 ‐0.091 ‐0.671** ‐0.606* ‐0.274 ‐0.869** % D. potatorum ‐0.273 ‐0.019 ‐0.302 ‐0.461 ‐0.105 ‐0.442 % Cystophora spp. ‐0.379 ‐0.347 ‐0.365 0.232 0.305 ‐0.134 % Sargassum spp. ‐0.263 ‐0.085 ‐0.198 ‐0.057 0.066 0.492 % Understorey mixed reds 0.714** 0.293 0.68** 0.541 0.402 0.72** % Understorey mixed greens 0.123 0.761** 0.491 0.24 ‐0.131 ‐0.055 % Understorey mixed browns ‐0.417 ‐0.677* ‐0.757** ‐0.343 0.078 ‐0.569 % Understorey branching corallines ‐0.312 ‐0.208 0.126 0.199 0.309 ‐0.027 % Sessile invertebrates 0.438 0.623* 0.812** 0.699** 0.514 0.442

Rock Lobster Habitat Assessment 58

Discussion

Underwater Video Survey Linking Habitat and CPUE Data It is important to note the limitations of Multivariate and univariate approaches were underwater video collected during this project. used to relate differences in habitat between the Factors including turbidity, light attenuation rock lobster fixed sites to differences in cpue in with depth and maintaining camera stability these areas. A broad‐scale approach had to be were the primary factors limiting interpretation adopted to link habitats to cpue as the lack of the video footage. Water clarity was most positional data for the zero catches meant that a affected by turbidity at the inshore sites (e.g. fine‐scale approach linking individual pot Warrnambool South and Warrnambool West) catches to the surrounding reef habitat within a where wave energy had stirred up sediment in fixed site was not possible. the water column. Water clarity improved with The multivariate approach indicated that there distance from shore and the deepest sites had the was a lot of redundancy in the habitat data. A clearest water. It was often only the canopy smaller subset of habitat parameters was able to species that were clearly visible in the summarise the relationship between sites and underwater video at sites dominated by large maintain the pattern of the sites where they brown macroalgae (e.g. kelps) due to the could be grouped by depth and mean cpue. A understorey biota being obscured by the canopy number of these habitat parameters identified as species. being potentially important in the multivariate Despite these limitations, the video surveys analysis were also found to be significantly provided the first comprehensive habitat survey correlated with cpue in three out of the six years. of the rock lobster fixed sites. Distinct habitat These variables were depth, proportion of assemblages that could be linked to depth were continuous rocky reef, percentage cover of P. identified across the fixed sites. The depth comosa, percentage cover of understorey red zonation of the dominant reef communities was algae and percentage cover of sessile consistent with previous video observations and invertebrates and are all potentially important in habitat mapping in western Victoria (e.g. Ball determining rock lobster distributions. and Blake 2007, Holmes et al. 2007a, b, Surprisingly the proportion of continuous rocky Ierodiaconou et al. 2007). reef was negatively correlated with cpue of rock This project found extensive sessile invertebrate lobster. The proportion of patchy reef was communities (sponge beds) at the deep sites (i.e. positively correlated with cpue in three years, Discovery Bay Deep, Port Fairy Deep, Nine Mile although the correlation coefficient in 2005 was Reef). There has been limited research on sponge just below the arbitrary cut‐off value of 0.6 for and ecology in Bass Strait (e.g. further investigation (Table 6). Overlaying the Wiedenmayer 1989). Butler et al. (2002) found proportion of patchy reef on the nMDS that the spatial distributions of sessile faunal ordination did not suggest that patchy reef assemblages (including sponge beds) in Bass contributed to the grouping of the sites. Strait are unknown. The video surveys in this However, the proportion of video transects that project indicated that sponge beds are recorded primarily patchy reef was in direct widespread in the western zone and are contrast to the proportion that recorded important habitats at deep rock lobster fishing primarily continuous reef (Figure 26). As a areas. consequence, it is more likely that the negative correlation with continuous reef actually Hydro‐acoustic mapping at Warrnambool West reflected the positive relationship between rock highlighted the additional seabed information lobster and the presence of patchy reef. The that can be produced by these systems. Deakin University analysis at Warrnambool Overlaying the rock lobster pot locations on South also found that higher rock lobster habitat mapping from the sidescan sonar showed a suitability was linked to the fore reef of Hopkins pattern of fishing effort that was consistent with Bank at the interface with the adjacent sediment previous observations on the importance of reef and deeper isolated reef patches (Appendix 2). edges as rock lobster habitat (see below). Jasus edwardsii has been described as foraging

Rock Lobster Habitat Assessment 59

over sand flats at night and returning to reef and adults (Jenkins et al. 2005). While reefs with a shelters by day (reviewed in Jenkins et al. 2005). high cover of sessile invertebrates often appear to Kelly et al. (1999) also described the use of reef provide little in the way of reef shelters (e.g. edges by J. edwardsii to maximise the physical Figures 6k and 17f), a combination of sponge protection they received from the reef. Patchy beds on patchy reef may provide access to both reef may therefore provide greater foraging shelter at the reef edges and good foraging opportunities due to the proximity of sand opportunities in the sponge beds (e.g. Figure habitat and the reef edges might offer a good 17d). source of cover for rock lobster. There was a fairly consistent positive relationship Three biotic parameters correlated with cpue (i.e. between cpue values and depth, with higher P. comosa, understorey red algae and sessile catches at greater depths. There were also invertebrates). Despite the problems with positive correlations between the percent cover accurately identifying understorey species with of understorey red algae and sessile invertebrates video surveys, there was still a strong with depth (r = 0.605 and 0.756 respectively) and relationship between cpue and the observed red these parameters may be driving the relationship algae understorey. The proportion of P. comosa between depth and cpue. A more intensive recorded in the quadrats was strongly negatively sampling design incorporating a greater range of correlated with the proportion of red algae depths would help assess the importance of these understorey (r = ‐0.805). This was in part because habitats to rock lobster. where there was a high percentage cover of Alternatively, it is possible that deeper areas are macroalgae the understorey was hard to see in less frequently fished and that densities really are the video (e.g. Figure 8j). There were also greater at increased depths. Unfished marine relatively few sites that had a high cover of P. protected areas could be investigated to test this comosa (Figure 27) and it is likely that the possibility. Apart from the increased fuel costs negative relationship between cpue and P. comosa associated with travelling further to an offshore may just reflect the positive relationship between fishing ground, rock lobsters from deeper areas red algae and cpue. in Victoria are of lower value due to their lighter Red algae have been shown to provide important colouration, so there are economic reasons for habitat for newly settled and juvenile lobster in targeting inshore areas (D. Hobday pers. comm.). previous studies (Jenkins et al. 2005). It is possible The habitats at similar depths were also similar that there may be relatively little migration away across the sites. This was not surprising as most from settlement areas at the scale considered here of the rock lobster fixed sites surveyed in this which would explain the correlation between project fell within as single meso‐scale marine adult densities and the red algae understorey. bioregion i.e. Otway region (IMCRA Technical Sessile invertebrates (sponge communities) have Group 1998). The Ocean Grove‐Torquay fixed been shown to provide important habitat for site in the eastern fishing zone was the only site spiny lobster in other studies (Herrnkind et al. that fell within the adjacent Central Victoria 1997, Lipcius et al. 1997, Eggleston and Dahlgren bioregion. 2001) and also features in the diet of juveniles

Rock Lobster Habitat Assessment 60

Conclusions

This project collected baseline information on Acoustic mapping systems (e.g. sidescan and habitat characteristics at the rock lobster fixed multibeam sonar) can provide total survey sites that will be important for future monitoring. coverage of the seabed. The recent Victorian Marine Habitat Mapping Project surveyed over Due to the nature of the available catch data, the 1,200 km2 of the seabed in 14 regions across analysis presented here was at a broad scale Victoria with multibeam sonar from 2005 to 2008. comparing differences in habitat between fixed This mapping project has produced high‐ sites to differences in catch rates. Recording the resolution bathymetry and detailed substratum position of the zero catches in the rock lobster and biological habitat data for many of the highly database would enable a fine‐scale (within reef) productive rock lobster fishery areas in the analysis of habitat use and potential species western and central zones. The pilot study interactions. conducted by Deakin University for this project A combination of multivariate and univariate has highlighted the potential for further analyses suggested that a subset of habitat investigations of rock lobster habitats through parameters (i.e. depth, amount of patchy reef, P. integration of catch data with the multibeam comosa, understorey red algae and sessile spatial habitat data. invertebrates) may be important in determining Future surveys of the rock lobster fixed sites rock lobster distributions. The analysis suggested would improve the understanding of habitat that the amount of patchy reef, red algae and characteristics across sites and allow a more sessile invertebrates should be the focus of any targeted sampling approach for the annual future fine‐scale studies that attempt to relate fishing surveys. individual pot catch to habitat data. The distribution of red algae and sessile invertebrates There is currently a spatial overlap in the areas also seemed to be related to depth in this project fished for the Torquay and Ocean Grove fixed and a more rigorous stratified sampling regime sites. Torquay and Ocean Grove had would be required to investigate these potential considerable differences in cpue and so it is habitat associations in more detail. recommended that a clear spatial boundary be established between these sites to enable these This project only investigated the relationship differences to be investigated in more detail. A between physical and biological habitat and rock possible boundary could be created based on a lobster catches. Oceanographic influences natural break in the nearshore reef by extending including wave energy and nutrient rich a boundary directly south from Bancoora Beach upwellings may be strongly linked to the (Longitude 144° 24ʹ 35ʺ, GDA94). recruitment of rock lobsters which, in turn, may be linked to adult densities (Hobday et al. 2006). Incorporating oceanographic measures at each of the fixed sites may provide further information about important habitat for rock lobsters.

Rock Lobster Habitat Assessment 61

Acknowledgements

The following rock lobster fishers and charter Malaguerra 3 (Discovery Bay Deep), Russel boat operators are thanked for their participation Williams Perceive (Port Fairy Deep), Gerhard in this study; Mick Astbury Tanamerah Wilmink Johanna Cherrie (Nine Mile Reef & Big (Warrnambool West), Les Feast Rudie Marie Reef). (Discovery Bay West), Ian Garland Reel Easy David Hatton and Richard Gasior participated in (Ocean Grove & Torquay), Dean Humphries the underwater video surveys. David Hobday Heritage (Portland), Lenny Lucas Amanda Louise and Rhonda Flint assisted with access to the rock (Warrnambool South), Alan Moncrieff Ocean lobster fixed site survey data. Endeavour (Warrnambool East), Howard Sharp Crustacea (Port Fairy West), Paul Vandepeer M.

Rock Lobster Habitat Assessment 62

References

Interim Marine and Coastal Regionalisation for Eggleston, D.B., and Dahlgren, C.P. (2001). Australia Technical Group (1998). Interim marine Distribution and abundance of Caribbean spiny and coastal regionalisation for Australia: An lobsters in the Key West National Wildlife ecosystem‐based classification for marine and Refuge: relationship to habitat features and coastal environments. Version 3.3, Environment impact of an intensive recreational fishery. Australia, Commonwealth Department of the Marine and Freshwater Research 52, 1567–76. Environment, Canberra. Fish, J.P., and Carr, H.A. (1990). ‘Sound Ball, D., Blake, S., and Plummer, A. (2006). underwater images. A guide to the generation Review of marine habitat classification systems. and interpretation of side scan sonar data.’ Parks Victoria Technical Series No. 26, (American Underwater Search and Survey Ltd, Melbourne. Lower Cape Publishing, Orleans MA, USA). Ball, D., and Blake, S. (2007). Shallow water Fish, J.P., and Carr, H.A. (2001). ‘Sound habitat mapping at Victorian Marine National reflections: advanced applications of side scan Parks and Marine Sanctuaries, Volume 1: sonar.’ (Lower Cape Publishing, Orleans, MA, Western Victoria. Parks Victoria Technical Series USA). No. 36, Melbourne. Ierodiaconou, D., Burq, S., Reston, M., and Blondel, P., and Murton, B.J. (1997). ‘Handbook Laurenson, L. (2007). Marine benthic habitat of seafloor sonar imagery.’ Wiley Praxis Series in mapping using multibeam data, georeferenced Remote Sensing. (John Wiley and Sons). video and image classification techniques in Victoria, Australia. Journal of Spatial Science 52, Bohnsack, J.A. (1979). Photographic quantitative 93–104. sampling of hard‐bottom benthic communities. Bulletin of Marine Science 29, 242–252. Jenkins G.P., Morris L.C., and Blake S. (2005). Ecological risk assessment of the Victorian rock Butler, A., Althaus, F., Furlani, D., and Ridgway, lobster fishery. Fisheries Victoria Research K. (2002). Assessment of the conservation values Report Series 28, Melbourne. of the Bass Strait sponge beds area. A component of the Commonwealth Marine Conservation Hart S.P., Edmunds M., Ingwersen C., and Elias Assessment Program 2002–04. Report to J. (2004). Victorian subtidal reef monitoring Environment Australia, CSIRO Marine Research, program: The reef biota on the Western Victorian Hobart. Coast. Parks Victoria Technical Series No. 14, Parks Victoria, Melbourne. Clarke, K., and Warwick, R. (2001). ‘Change in Marine Communities: An Approach to Statistical Herrnkind, W.F., Butler, M.J., Hunt, J.H., and Analysis and Interpretation. (2nd Edition, Childress, M. (1997). Role of physical refugia: PRIMER‐E, Plymouth). implications from a mass sponge die‐off in a lobster nursery in Florida. Marine and Freshwater Danforth, W.W. (1997). Xsonar/ShowImage: A Research 48, 759–769. complete system for rapid side scan sonar processing and display, U.S. Geological Survey, Hobday, D., and Morison, A. (2006). Victorian Open File Report 97–686. fisheries assessment report, Rock Lobster 2006. Fisheries Victoria Assessment Report Series No. Department of Primary Industries (2003). Rock 51. Queenscliff. lobster fishery management plan, 2003. Compiled by the Rock Lobster and Giant Crab Hobday, D.K., Frusher, S.D., and Linnane, A. Fishery Management Plan Steering Committee. (2006). Can production in the southern rock Fisheries Victoria Management Report Series, lobster fishery be improved? Linking juvenile No.1, Melbourne. growth, survival and density dependence to sustainable yield. Final report to Fisheries Department of Primary Industries (2008). Draft Research and Development Corporation Project Victorian rock lobster fishery management plan No. 2001/070. Primary Industries Research 2008. Fisheries Victoria Management Report Victoria, Queenscliff. Series No. 58, Melbourne.

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Holmes, K.W., Grove, S.L., Van Niel, K.P., and Kendrick, G.A. (2007a). Mapping the benthos in Victoria’s Marine National Parks. Volume 3: Point Addis Marine National Park. Parks Victoria Technical Series No. 42. Parks Victoria, Melbourne. Holmes, K.W., Radford, B., Van Niel, K.P., Kendrick, G.A., and Grove, S.L. (2007b). Mapping the benthos in Victoria’s Marine National Parks, Volume 5: Discovery Bay Marine National Park. Parks Victoria Technical Series No. 44. Parks Victoria, Melbourne. Kelly, S., MacDiarmid, A.B. and Babcock, R.C. (1999). Characteristics of spiny lobster, Jasus edwardsii, aggregations in exposed sandy areas. Marine and Freshwater Research 50, 409–416. Leonard, G.H. and Clark, R.P. (1993). Estimating cover of benthic red algae. Marine Ecology Progress Series 101, 203–208. Lipcius, R.N., Stockhausen, W.T., Eggleston, D.B., Marshall jr, L.S., and Hicked, B. (1997). Hydrodynamic decoupling of recruitment, habitat quality and adult abundance in the Caribbean spiny lobster: source‐sink dynamics? Marine and Freshwater Research 48, 807–815. Rattray, A., Ierodiaconou, D., Laurenson, L., Burq, S., Reston, R. (in press). Mapping benthic biological communities using multi‐beam sonar, video data and a decision tree classification method on the temperate south‐east Australian continental shelf, Estuarine Coastal and Shelf Science, doi:10.1016/j.ecss.2009.06.023. Wiedenmayer, F. (1989). Demospongiae from northern Bass Strait, southern Australia. Memoirs of .Museum of Victoria 50, 1–242. Witman, J.D., and Sebens, K.P. (1992). Regional variation in fish predation intensity: a historical perspective in the Gulf of Maine. Oecologia 90, 305–315.

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Appendix 1 – Video Database Metadata

Table 7. Video survey database attributes.

Attribute Description Value Loc_id Video site ID Site initials of fixed site and numeric code for video site RL_mon_site Rock lobster fixed site Site name Vessel Video survey vessel Vessel name Fisher Commercial fisher for the fixed site Fisher name Date Date of the video survey Date Quad_utc Video survey time at quadrat position from GPS UTC time Q_lat_deg Quadrat latitude ‐ degrees (WGS84) Degrees Q_lat_min Quadrat latitude ‐ decimal minutes (WGS84) Decimal minutes Quad_Lat Quadrat latitude ‐ decimal degrees WGS84 Decimal degrees Q_long_deg Quadrat longitude – degrees (WGS84) Degrees Q_long_min Quadrat longitude – decimal minutes (WGS84) Decimal minutes Quad_Long Quadrat longitude ‐ decimal degrees WGS84 Decimal degrees Quad_Depth Video quadrat depth Metres T_L_end_dg Transect end latitude ‐ degrees (WGS84) Degrees T_L_end_mn Transect end latitude ‐ decimal minutes (WGS84) Decimal minutes T_end_lat Transect end latitude ‐ decimal degrees (WGS84) Decimal degrees T_Ln_end_d Transect end longitude ‐ degrees (WGS84) Degrees T_Ln_end_m Transect end longitude ‐ decimal minutes (WGS84) Decimal minutes T_end_long Transect end longitude ‐ decimal degrees (WGS84) Decimal degrees Transect ‐ Substratum Type and Structure T_Rck_Reef Continuous Rock/Reef ‐ consolidated substratum. Percentage of transect T_Rf_Pat_S Reef with patchy sand i.e. areas that had a higher Percentage of transect percentage of rock/reef coverage than sand. T_S_ Rf_pat Sand with patchy reef i.e. areas that had a higher Percentage of transect percentage of sand than rock/reef coverage. T_Sand Continuous sand. Percentage of transect T_hab_total Calculation of total percentage value from above 4 Combined value equals 100% transect substratum type and structure categories T_dom_sub Category (text) describing transect – “Patchy Rocky Text description Reef”, “Rocky Reef” or “Sediment”. Transect ‐ Substratum Category T_low_p_Rf Proportion of reef classified as low profile reef i.e. flat Percentage of total reef rocky reef with a profile predominantly <1 m. T_h_p_Rf Proportion of reef classified as high profile reef i.e. a Percentage of total reef profile predominantly>1 m. Transect ‐ Substratum Texture T_Conglom Conglomerate rock i.e. cobble/rubble consolidated Scale of 0‐3: together. 0 = None present T_Boulders Rocks with a diameter >250 mm 1 = <5% of transect T_Cobble Smooth rounded rocks with a diameter <250 mm 2 = 6 – 25% of transect T_Rubble Irregularly shaped rock fragments up to approximately 3 = >25% of transect 250 mm in diameter. T_Pinnacle A dramatic vertical rise of rock on all four pinnacle Scale of 0‐3: sides where the diameter does not exceed 5 m and rises 0 = No features present in excess of 3 m. 1 = Few features present <2

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T_Crks_Crv Cracks and crevices in reef, visible breaks or fractures 2 = Moderate features present 2– in the substratum. 4 T_Ldges_OH Ledges or overhangs in reef including rock that juts out 3 = Abundant features present >5 or is undercut. Transect ‐ Dominant Biota T_Dom_mac Dominant macro‐algae or other biota/vegetation based Species separated by “/” means on canopy species about equal cover of both, species separated by “>” means there was more of the first species. T_dom_code Letter code representing “T_dom_mac” used to label Codes separated by “/” mean maps in report about equal cover of both species, codes separated by “,” mean that there was more of the first species. T_SI Cover of sessile invertebrates High, Medium, Low, None

T_SI2 Presence/absence of sessile invertebrates 1 = absent, 2 = present T_Amphibolis Presence/absence of A. antarctica 1 = absent, 2 = present T_othr_bio Other biota Text description Quadrat Substratum Type and Structure Q_Rck_Reef Continuous rock/reef Q_Rf_pat_S Rocky reef with patchy sand Percentage of each category in Q_S_Rf_pat Sand with reef patches Quadrat Q_Sand Bare sand Quadrat ‐ Substratum Category Q_low_p_Rf Low profile reef i.e. flat rocky reef with a profile Percentage of total reef predominantly <1 m. Q_h_p_Rf High profile reef profile predominantly>1 m Percentage of total reef Q_map_cat Descriptive category (text) for the quadrat High Profile Reef, Low Profile Reef, Low Profile Reef – Patchy or Sediment. Quadrat – Substratum Texture Q_Crks_Crv Cracks and crevices i.e. visible breaks or fractures in the Percentage of quadrat substratum Q_Ldges_OH Ledges or overhangs including rock that juts out or is Percentage of quadrat undercut. . Q_Conglom Conglomerate cobble or rubble that is consolidated Percentage of quadrat together. Q_Boulders Rocks with a diameter >250 mm Percentage of quadrat Q_Cobble Smooth rounded rocks with a diameter <250mm Percentage of quadrat Q_Rubble Irregularly shaped rock fragments up to approximately Percentage of quadrat 250mm in diameter Quadrat ‐ Dominant Biota Q_up_canop Quadrat upper canopy ‐ percentage of large brown Percentage of quadrat (Phaeophyta) macroalgae Q_understy Quadrat understorey – percentage of the combined Percentage of quadrat understorey brown (Phaeophyta), red (Rhodophyta) and green (Chlorophyta) algae. The cover estimate was restricted to the understorey visible in the video footage. The actual coverage of understorey algae may be greater where it is hidden by the upper canopy. Q_encrust_cl Encrusting coralline algae. This algae could not be Percentage of quadrat

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identified to genus level from the video so it was grouped into this single category. Q_bare_Rf No visible biota or sediment on the rock. Percentage of quadrat Q_unknown Percentage of quadrat where the algae category could Percentage of quadrat not be identified. Q_biota Other biota e.g. sessile invertebrates, seastars etc. Percentage of quadrat Q_unv_Sd_C Bare sediment in quadrat. Percentage of quadrat Q_tot_Biota Calculation of total percentage values from the above This should equal 100% categories. Quadrat – Canopy Biota Q_up_Ecklo Coverage of E. radiata in upper canopy. Percentage of the quadrat upper canopy. Q_up_Phyll Coverage of P. comosa in upper canopy. Percentage of the quadrat upper canopy. Q_up_Durvl Coverage of D. potatorum in upper canopy. Percentage of the quadrat upper canopy. Q_up_Macro Coverage of Macrocystis angustifolia in upper canopy. Percentage of the quadrat upper canopy percentage. Q_up_Cysto Coverage of Cystophora spp. in upper canopy. Percentage of the quadrat upper canopy. Q_up_Sarg Coverage of Sargassum spp. in upper canopy. Percentage of the quadrat upper canopy. Q_tot_Upper Calculation of total percentage values from the above 6 This should equal 100% categories. Quadrat – Understorey Biota Q_un_mx_ rd Mixed red (Rhodophyta) algae within the understorey. Percentage of quadrat understorey Q_un_mx_gr Mixed green (Chlorophyta) algae within the Percentage of quadrat understorey. understorey Q_un_mx_br Mixed brown (Phaeophyta) algae within the Percentage of quadrat understorey. understorey Q_un_br_cr Branching coralline algae within the understorey. Percentage of quadrat understorey Q_un_undef Coverage of the understorey which could not Percentage of quadrat identified. understorey Q_tot_Under Calculation of total percentage values from the above This should equal 100% understorey categories. Q_SI Percentage cover of sessile invertebrates within Percentage cover in quadrat quadrat. Q_seastar Number of sea stars (Asteroids) within quadrat. Total number Transect ‐ Other Biota T_Old_Wife Number of old wifes Enoplosus armatus sighted Total number T_Old_Wife2 Presence of old wifes 1 = none sighted, 2 = sighting T_Seastar Number of sea stars Asteroids spp. sighted Total number T_Seastar2 Sighting of sea stars 1 = none sighted, 2 = sighting T_Sweep Number of sweep Scorpis spp. sighted Total number T_Sweep2 Sighting of sweep 1 = none sighted, 2 = sighting T_Mag_per Number of magpie perch Cheilodactylus nigripes sighted Total number T_Mag_per2 Sighting of magpie perch 1 = none sighted, 2 = sighting T_But_Per Number of butterfly perch Caesioperca lepidoptera Total number (includes text (school) and/or >5) T_But_Per2 Sighting of butterfly perch 1 = none sighted, 2 = sighting T_Bl_wrass Number of blue–throated wrasse Notolabrus tetricus Total number

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T_Bl_wrass2 Sighting of blue‐throated wrasse: 1 = none sighted, 2 = sighting T_Wrasse Sighting of other species of wrasse Total number T_Wrasse2 Sighting of other wrasse species: 1 = none sighted, 2 = sighting T_Pike Number of long‐finned pike Dinolesties lewini Total number T_Pike2 Sighting of long‐finned pike: 1 = none sighted, 2 = sighting T_Mrb_fish Number of marble fish Aplodactylus arctidens Total number T_Mrb_fish2 Sighting of marble fish: 1 = none sighted, 2 = sighting T_Moonligh Number of moonlighters Tilodon sexfasciatus Total number T_Moonligh2 Sighting of moonlighters: 1 = none sighted, 2 = sighting Other Information Q_fr_grab_down Screen grab taken from downward looking camera at JPG file name(s), (N = no image) Quadrat location.

T_fr_grab_side Screen grab taken from sideward looking camera. JPG file name(s), (N = no image) Comments Any additional comments. Text T_length_m Length of video transect Metres

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Appendix 2 – Deakin University Report

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Preliminary spatial analysis of rock lobster catch data for the Hopkins Bank

Alex Rattray, Jacquomo Monk, Daniel Ierodiaconou

Deakin University, School of Life and Environmental Sciences Warrnambool Campus

4 August 2009

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Background The Victorian Marine Habitat Mapping Project surveyed over 1,200 km2 in 14 regions within Victorian state waters from 2005 to 2008. The project conducted multibeam sonar surveys and underwater video ground‐truthing to investigate the distribution and complexity of seabed habitats. Seascape metrics were derived for each site and used for the classification of substrata and biota using automated classification techniques (Rattray et al. in press). The survey regions included a site at Hopkins Bank which overlapped the Warrnambool South rock lobster fixed site (Ierodiaconou et al. 2007). Substrata and dominant biota maps for the Hopkins Bank site are shown in Figures 1 and 2 respectively. The Fisheries Victoria Fisheries Research Branch (FRB) provided Deakin University, School of Life and Environmental Sciences with a grant to undertake a pilot study to assess potential spatial analysis techniques for integrating rock lobster fixed site catch and multibeam sonar habitat data to investigate rock lobster habitat preferences at the Warrnambool South/Hopkins Bank site.

Figure 1. Substrata classification using an automated decision tree classification approach.

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Figure 2. Dominant biota classification using an automated decision tree classification approach.

Spatial Autocorrelation Analysis Rock lobster total catch (Total_N) figures were tested for spatial autocorrelation using global Moran’s I index for each year individually and also the entire dataset comprising years 2002 to 2007 at threshold distances between 150 and 1,000 m (Table 1.). Moran’s I measures dependence based on both feature locations and feature values simultaneously. Given a set of features and an associated attribute, it evaluates whether the pattern expressed is clustered, dispersed, or random under a null hypothesis of complete spatial randomness. Years 2003, 2004, 2006, 2007 and combined years (2002–07) were found to exhibit significant spatial autocorrelation, violating the assumption of independent sample data and therefore precluding the use of parametric statistical tests.

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Table 1. Moranʹs I index and Z‐score for Total_N (Bold values indicate significant spatial clustering)

Threshold distance 150 m 300 m 600 m 1,000 m Year I index Z score I index Z score I index Z score I index Z score 2002 ‐0.22 ‐1.47 ‐0.12 ‐0.98 ‐0.04 ‐0.26 ‐0.04 ‐0.27 2003 0.24 2.28 0.1 2.83 0.14 2.97 0.11 2.92 2004 0.08 0.88 0.1 1.69 0.06 1.65 0.04 1.46 2005 ‐0.04 0.23 ‐0.01 0.11 ‐0.05 ‐0.65 ‐0.04 ‐0.61 2006 0.31 3.08 0.3 4.45 0.27 5.44 0.25 5.73 2007 0.28 2.54 0.26 3.39 0.22 3.99 0.2 4.71 All 0.2 6.57 0.18 8.71 0.16 9.97 0.13 9.63

Spatial autocorrelation values were used to select appropriate range thresholds (ranges exhibiting high spatial autocorrelation) for input into Getis‐Ord hotspot analysis. Given a set of weighted features, the Getis‐Ord Gi* statistic identifies spatial clusters of high values (hot spots) and spatial clusters of low values (cold spots). The local sum for a feature and its neighbors is compared proportionally to the sum of all features; when the local sum is much different than the expected local sum, and that difference is too large to be the result of random chance, a statistically significant Z score results. Significant spatial clustering of high Total_N values is observed in the north western area of the study site, while spatial clustering of low Total_N values occurs in the south western portion of the bank feature excepting years 2002 and 2005 which show only weak clustering (Figures 3–9). Outputs from these analyses should be interpreted with care due to underlying (i.e. fishery dependent) bias in the sampling regime.

Figure 3. Year 2002 ‐ Getis‐Ord Gi* statistic (rendered z‐scores) calculated using total Rock lobster (Total_N) catch.

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Figure 4. Year 2003 ‐ Getis‐Ord Gi* statistic (rendered z‐scores) calculated using total Rock lobster (Total_N) catch.

Figure 5. Year 2004 ‐ Getis‐Ord Gi* statistic (rendered z‐scores) calculated using total Rock lobster (Total_N) catch.

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Figure 6. Year 2005 ‐ Getis‐Ord Gi* statistic (rendered z‐scores) calculated using total Rock lobster (Total_N) catch.

Figure 7. Year 2006 ‐ Getis‐Ord Gi* statistic (rendered z‐scores) calculated using total Rock lobster (Total_N) catch.

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Figure 8. Year 2007 ‐ Getis‐Ord Gi* statistic (rendered z‐scores) calculated using total Rock lobster (Total_N) catch.

Figure 9. Years 2002‐2007 ‐ Getis‐Ord Gi* statistic (rendered z‐scores) calculated using total Rock lobster (Total_N) catch.

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Ecological Niche Factor Analysis (ENFA) Ecological Niche Factor Analysis (ENFA) first proposed by Hirzel et al. (2002) is an alternative approach to modelling distributions of species where no reliable absence data exist. Suitability functions (envelopes) are computed by comparing predictor raster datasets which underlie species distributions and comparing them to the analysis extent as a whole (see Hirzel and Arlettaz 2003). Eco‐geographical predictor variables (3x3 analysis scale) selected for input to the model were bathymetry, backscatter, HSI (r,g,b), complexity, slope, aspect (northness, eastness), rugosity, maximum curvature, Benthic Position Index (BPI) , Euclidean distance to reef (Figure 10) and predicted biotic habitats (Figure 11). Eco‐geographical variables were derived from multibeam sonar data collected as part of the Victorian Marine Habitat Mapping Project (see Ierodiaconou et al. 2007). A Box‐Cox transformation was applied to normalise all derivatives of the multibeam data and a correlation matrix was calculated for the predictor variables to avoid inputting redundant information to the model (correlation threshold: r = 0.5, Figure 12). Predictor variables omitted from the model building process due to correlation values over the threshold were HSI‐red, HSI‐green and substrata. Bathymetry and backscatter were also found to be correlated (although this may not hold true for other sites). Backscatter was selected as a predictor variable more suitable to the study at hand and bathymetry was therefore removed from the analysis process.

Figure 10. Euclidean distance (m) to reef.

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Figure 11. Predicted biological habitats.

Figure 12. Correlation analysis of Eco‐geographic variables retained for model development

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Three factors were retained on the basis of comparison with the ‘broken stick’ distribution (Hirzel et al. 2002). The three factors retained accounted for 83.9% of the sum of the eigenvalues. The factor analysis permits the extraction of linear combinations of the original variables, on which the focal species shows most of its Marginality (M) and Specialization (S). M represents the ecological distance between the species optimum and the mean habitat within the reference area (Hirzel et al. 2002). The overall marginality was 0.604, whilst the specialisation was 1.335, with a tolerance of 0.749. These results indicate that rock lobster habitat suitability differs considerably from the mean environmental conditions over the study area; however, it exhibits a relatively wide ranging habitat niche. The eco‐geographic variables that most determined the presence of rock lobster, in order of importance were Backscatter, Euclidean distance to reef, rugosity and slope (see table 2). Examination of the size (i.e >0.1) and sign (i.e +/‐ values) for each eco‐geographical variables indicates the contribution and preferred range of values relative to the global mean for that particular variable. Marginality coefficients showed that cells representing rock lobster presence were linked to lower backscatter returns (‐0.79), and closer proximity to reef (‐0.42), whilst rugosity and slope were greater than the global mean for these measures (table 3). Importantly, the inverse relationship between rock lobster catches and proximity to reef show a preference for locations near reef (mean distance 20 metres). This may not be a true reflection of habitat preference but a function of fishing practices (i.e. unwillingness to lose gear on heavy ground, weather conditions or targeting reef breaks (inflexion)).

Table 9. Amount of specialisation explained by the first three factors

Predictor Variable Factor 1 Factor 2 Factor 3 M (100%), S (37%)* S (20%) S (11%)

Backscatter ‐0.79 0.19 0.41 Euclidean Distance to reef ‐0.42 0.1 ‐0.66 Rugosity 0.24 ‐0.13 0.02 Slope 0.23 0.93 ‐0.13 HSI‐r 0.14 0.21 0.56 Complexity 0.14 ‐0.12 ‐0.08 BPI 0.11 ‐0.01 ‐0.1 Maximum Curvature 0.11 ‐0.01 0.02 Northness ‐0.11 0.05 ‐0.08 Eastness ‐0.1 ‐0.01 ‐0.07 Biota 0.03 ‐0.02 ‐0.16 *M= marginality; S= specialisation

Table3. Distribution of values of ecological important variables identified by ENFA

Species Global Ecogeographical variable Mean SD Mean SD Backscatter ‐147.01 4.6509 ‐140.99 6.7046 Euclidean Distance to reef 20.102 41.407 52.493 70.381 Rugosity 1.0041 0.0070126 1.0024 0.0053642 Slope 2.5677 2.1779 1.8366 1.7751

The model indicates that higher rock lobster habitat suitability is linked to the fore reef of the Hopkins Bank (Figure 13a,c.). Suitability is also linked to isolated reef patches in deeper regions south of the bank; however effects of variation in patch size were unable to be accounted for with the available data. In general, reef crests show low habitat suitability. Features in the northwestern zone of the study area show

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a steep reef inflexion (Figure 13b.) with pronounced reef‐sediment interface. High habitat suitability of areas of flat sediment in this zone may be attributed to targeting of the adjacent reef structure. The results of a jack‐knife cross‐validation procedure (Boyce et al. 2002) for the overall curve suggest that the model robustness is acceptable (Boyce index = 0.90± 0.13). Care must be taken in measures of confidence as the rock lobster catch data set is not fully representative of lobster habitat.

a.

b. c.

Figure 13. a. habitat suitability (%) for rock lobster (Total_N) on the Hopkins Bank; b. cliff feature with bathymetric cross‐section; c. bathymetric cross section of Hopkins Bank.

Limitations and Potential Research Direction Rock lobster catch data showed spatial clustering across most years investigated using global autocorrelation statistics. The rock lobster dataset therefore violates the assumption of independence and parametric statistical methods are not suitable for analysis. Ecological Niche Factor Analysis is seen as a viable modelling alternative as algorithms make no assumptions as to the shape of species distribution or the density of the observations. However it is required that the observation data is representative of the target species ecological niche if we are to model true habitat suitability. Results derived from this study indicate that lobster habitat suitability differs considerably from the mean environmental conditions over

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the study area. These results cannot however be interpreted in terms of rock lobster habitat suitability per se, but rather a function of fisheries dependent data which may be confounded by a number of factors surrounding targeted fishing effort. All models derived using this data set may better represent an element of rock lobster ‘catchability’. In order for habitat suitability models to more accurately reflect actual habitat suitability for this species future sampling regimes would require an alternative (randomised) strategy. This is not to say that available fisheries data cannot be meaningfully analysed using these methods, rather that questions asked of the data must be carefully defined. All tests and analyses in this study were carried out using total number of rock lobster trapped (Total_N). The use of other metrics within the dataset (e.g. kg legal/ undersized) may yield different suitability patterns, although the data are still likely to exhibit spatial autocorrelation. Whilst similar analysis windows used in this analysis (3 x 3 kernel size) has been shown to influence rock lobster distribution in previous studies (e.g. Galparsoro et al. 2009), the use of analysis windows at different spatial scales may better capture the effects of these eco‐geographical variables on habitat suitability (Wilson et al. 2007). The relationship between rock lobster data and eco‐geographic variables may share some commonality between sites; however site specific observation data will be required to test the robustness of model outputs and the importance of variable influence. The inclusion of other bathymetry derived environmental variables such as exposure should be considered as well as oceanographic variables from other sources (e.g. wave currents, temperature and wind) as suggested by Galparsoro et al. (2009).

References Boyce M.S, Vernier P.R, Nielsen S.E, Schmiegelow F.K.A. (2002). Evaluating resource selection functions. Ecological Modelling 157, 281–300. Galparsoro I, Borja A, Bald J, Liria P, Chust G. (2009). Predicting suitable habitat for the European lobster (Homarus gammarus), on the Basque continental shelf (Bay of Biscay), using Ecological‐Niche Factor Analysis. Ecological Modelling 220, 556–567 Hirzel A.H, Hausser J, Chessel D, Perrin N. (2002). Ecological‐niche factor analysis: How to compute habitat‐suitability maps without absence data? Ecology 83, 2027–2036. Hirzel A.H, Arlettaz, R. (2003). Modeling habitat suitability for complex species distributions by environmental‐distance geometric mean. Environmental Management 32, 614–623 Ierodiaconou D, Burq S, Laurenson L, Reston M. (2007). Marine habitat mapping using multibeam data, georeferenced video and image classification techniques: A case study in south‐west Victoria. Journal of Spatial Sciences, 52, 93–104. Rattray, A., Ierodiaconou, D., Laurenson, L., Burq, S., Reston, R. (in press). Mapping benthic biological communities using multi‐beam sonar, video data and a decision tree classification method on the temperate south‐east Australian continental shelf, Estuarine Coastal and Shelf Science, doi:10.1016/j.ecss.2009.06.023. Wilson M.F.J, O’Connell B, Brown C, Guinan J.C, Grehan A. (2007). Multiscale terrain analysis of multibeam bathymetry data for habitat mapping on the continental slope. Marine Geodesy 30, 3–35.

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