Habitat associations and distribution of the hyperbenthic shrimp, Nauticaris marionis, around the sub-Antarctic Prince Edward Islands

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Habitat associations and distribution of the hyperbenthic shrimp, Nauticaris marionis, around the sub-Antarctic Prince Edward Islands ⁎

Craig Haleya,b, Charles von der Medenb, Lara Atkinsona,b, , Cecile Reeda Marine Research Institute (Ma – Re), Biological Sciences Department, University of Cape Town, Rondebosch 7701, South Africa South African Environmental Observation Network, Egagasini Node, 5th flr Foretrust Building, Martin Hammerschlag Way, Private bag X2, Roggebaai, Cape Town 8001, South Africa a

b

A R T I C L E I N F O

A B S T R A C T

Keywords: Epibenthic assemblages Substratum type Depth Biogenic habitat Caridean shrimp, Southern Ocean

The association of organisms with particular habitats and habitat-forming organisms, can strongly influence species distributions, interactions and wider ecosystem services. At the sub-Antarctic Prince Edward Islands, the caridean shrimp Nauticaris marionis is a principal part of the benthic ecosystem, occurring between ca. 50 m and 600 m. Its role as a trophic link between the primary productivity and higher predators is established, but little is understood of its in situ habitat usage and associations or of how these structure patterns of abundance. We investigated these aspects directly using a benthic camera sled, sampling 27 stations between 50 m and 500 m. Substratum type was characterised, and estimates of percentage cover of the 13 main groups of habitat-forming epibenthic taxa were made, alongside absolute counts of N. marionis within ‘digital quadrats’ drawn from 300 m transects. The distribution of N. marionis was influenced by depth, substratum type and overall biogenic cover, being limited to habitats between 50 and 160 m depth on mud or gravel substrata only, and having > 50% biogenic cover. The presence/absence of N. marionis related to significantly different epibenthic assemblages (termed biogenic habitats), but this effect was contingent on depth. Likewise, densities of N. marionis were significantly affected by biogenic habitat type, identifying an association with two biogenic habitat groups, one dominated by red-algae, the other by structurally complex bryozoan species. These associations likely relate to the structural complexity of the two habitat groups, rather than the specific taxa involved. The apparent absence of N. marionis at depths > 160 m contrasts with earlier records and poses questions about the trophic importance of the shrimp in deeper habitats.

1. Introduction Associations of marine organisms with particular habitat types and habitat-forming species are known across coastal and deep-sea environments (e.g. Heck et al., 2003, Chittaro, 2004, Buhl-Mortensen and Mortensen, 2005, Ross and Quattrini, 2007, Buhl-Mortensen et al., 2010, Berkenbusch and Rowden, 2007, Wood et al., 2012). Identifying habitat use and associations, particularly within Vulnerable Marine Ecosystems (VMEs) of lesser known shelf and deep-sea areas, is relevant to wider ecological understanding and conservation planning (Tissot et al., 2006; Danovaro et al., 2008; Jones and Lockhart, 2011; Hughes et al., 2009). Benthic habitats are defined by both their abiotic and biotic characteristics (Diaz et al., 2004; Buhl-Mortensen et al., 2010). These two aspects of habitat can be closely related since, for example, the presence of structure-forming epibenthic assemblages can be influenced by both substratum type and depth (e.g. Sahade, 2004,

Mortensen and Buhl-Mortensen, 2004, Schlacher et al., 2007. Milligan et al., 2016). Structure-forming benthic organisms, such as cold water corals, provide a host of ecosystem functions in shelf and deep-sea benthic environments by enhancing physical habitat complexity, altering flow, providing nursery areas and refugia, increasing surface area for epibiotic colonisation and by increasing species diversity (Hixon and Beets, 1993; Steneck et al., 2002; Bradshaw et al., 2003; Tissot et al., 2006; Ross and Quattrini, 2007; Nagelkerken et al., 2008; Cole, 2010; Pirtle and Stoner, 2010; Miller et al., 2012; Thurber et al., 2014; Hemery and Henkel, 2015). As a consequence, habitat associations are known to occur between mobile and sessile organisms, such as between fish and deep cold water corals (Ross and Quattrini, 2007), and in coastal environments where dense seagrass stands host significantly more abundant aggregations of decapod crustaceans than bare stands (Lewis, 1984). Positive facilitation and feedback effects linked to habitat

⁎ Corresponding author at: South African Environmental Observation Network, Egagasini Node, 5th flr Foretrust Building, Martin Hammerschlag Way, Private bag X2, Roggebaai, Cape Town 8001, South Africa. E-mail address: [email protected] (L. Atkinson).

http://dx.doi.org/10.1016/j.dsr.2017.07.005 Received 8 March 2017; Received in revised form 12 July 2017; Accepted 17 July 2017 0967-0637/ © 2017 Published by Elsevier Ltd.

Please cite this article as: Haley, C., Deep-Sea Research Part I (2017), http://dx.doi.org/10.1016/j.dsr.2017.07.005

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improving understanding of relationships between the benthos, prey and foraging predators, as well as how future habitat changes may affect the marine ecology of the islands (Crawford et al., 2003; Hughes et al., 2009). For the purpose of this study, ‘habitat’ is defined as being a combination of substratum type and sessile epibenthic cover. By simultaneously characterising benthic habitats and quantifying the abundance of N. marionis across depth strata at the PEI, we assess its distribution and whether patterns of density of N. marionis are driven by habitat associations, depth effects or a combination of these factors.

2. Materials and methods 2.1. Field sampling and image processing A total of 27 benthic stations were sampled photographically during annual surveys in April-May 2013 and 2015. The locations of the stations (Fig. 1) were chosen to match a subset of sites surveyed historically by Branch et al. (1993). At each station, still images of the benthos were captured along a transect of approximately 300 m using a towed camera sled system (SkiMonkey III, Sea Technology Services (Pty) Ltd). This scale of sampling was deemed appropriate as it is substantially smaller than the scale of patchiness of benthic habitat types and assemblages identified by Branch et al. (1993) and observed during our sampling. The camera was fixed on a sled-type frame at a 30 degree angle relative to the horizontal plane, and images were taken in quick succession whilst steaming at approximately 0.5 knots, resulting in a series of non-overlapping oblique images along the transects. The area of seabed processed in each image was demarcated by a standard 50 × 50 cm digital quadrat, which, depending on the orientation of the camera, equated to real ground areas of between 0.33 and 0.46 m2. Tests of epibenthic species-area accumulation from the study area have confirmed that 20–25 images, which give a total sampled area of between 8.25 and 11.5 m2, ensure representation of approximately 80% of total species richness (Adams, 2017). The study area is comprised largely of unconsolidated sediments, allowing the substratum type at each station to be visually categorized as mud, gravel, rocky sand or rocky mud. In the absence of other major topographic features (boulders, cliffs etc.), these categories captured the main physical components of the benthic habitat. This general lack of emergent physical structures mean that complex habitat is largely provided by biogenic features. Between 20 and 25 high quality images were haphazardly selected from each transect and processed using point-count methodology and the software package Coral Point Count with Excel extensions (CPCe) version 4.1 (Kohler and Gill, 2006) to estimate the percentage cover of epibenthic structure-forming taxa. Only sessile epifaunal and macro-algal organisms with three-dimentional structure were recorded. By consulting species lists provided by Branch et al. (1993) as well as taxonomic keys for the benthic fauna of the PEI (Branch et al., 1991; Branch and Williams, 1993; Branch, 1994), 13 broad groups of taxa identified using our criterion encompassed the full range of emergent organisms present, including solitary and colonial forms. Groups included were: Porifera, Bryozoa, Hydrozoa, Polychaeta (colonial), Polychaeta (solitary but aggregated), Brachiopoda (solitary but aggregated), Crinoidea, green algae, red algae, and four Anthozoan groups (sea anemones, cerianthids, soft corals and sea fans). Absolute counts of N. marionis were simultaneously recorded within the same digital quadrat area from each image, allowing their respective densities to be calculated per square metre. Based on biologically linked topographic criteria, stations were binned into three depth strata, covering shallow (50–120 m, 8 stations), intermediate (121–299 m, 11 stations) and deep (300–500 m, 8 stations) locations. The shallow bin covered the euphotic zone and inner shelf which included areas with kelp and algae; the intermediate bin defined the inter-island saddle and margins, and the deep bin encompassed the slope habitats as far as the outer limit of sampling capability at 500 m.

Fig. 1. The sub-Antarctic Prince Edward Islands and locations of stations sampled during annual relief voyages in 2013 and 2015. Densities of Nauticaris marionis are indicated by the size of the station markers.

associations mean that species may be strongly dependent on particular habitat types, with far reaching implications in cases where the associating organisms are themselves functionally important (Stachowicz, 2001; Coleman and Williams, 2002; Berkenbusch and Rowden, 2007; Hughes et al., 2009). Regionally, the Prince Edward Islands and surrounding marine ecosystems (PEI, Fig. 1) are considered sentinels of climate change (Ansorge et al., 2014). Within this context the locally abundant hyperbenthic caridean shrimp, Nauticaris marionis, holds a functionally important trophic position by making poorly utilized primary productivity available to higher organisms (Perissinotto and McQuaid, 1990). While gut content analysis of N. marionis indicates that adults do not feed directly on phytoplankton, their megalope larvae do, and the majority of the adult's diet comprises of benthic suspension feeders and zooplankton (Pakhomov et al., 1999). At the same time, N. marionis is one of only a few benthic organisms preyed upon by diving macaroni penguins (Eudyptes chrysolophus), gentoo penguins (Pygoscelis papua), and occasionally Antarctic fur seals (Arctocephalus gazella), all of which can feed at depths over 100 m (Adams et al., 1993; Pakhomov and Froneman, 1999; Makhado et al., 2008; Pichegru et al., 2011). A combination of terrestrial nutrient inputs and hydrographic retention (island mass effect), result in regionally high levels of primary productivity that influence the benthos across the narrow shelf and slope habitats (Pakhomov and Froneman, 1999; Pakhomov et al., 2009). The areas close to the islands are vital for foraging predators (Adams et al., 1993; Espitalier-Noel et al., 1988) and predation of N. marionis means that some of the substantial primary productivity transferred to the seafloor can be taken up by these higher trophic levels (Perissinotto and McQuaid, 1990; Perissinotto, 1992). Although not endemic to the Prince Edward Islands, N. marionis has been found to be substantially more abundant at the PEI than at other sub-Antarctic islands (Probert et al., 1979; Arntz et al., 2006), and was found to be second in total benthic biomass only to bryozoans (Perissinotto and McQuaid, 1990). N. marionis readily occurs on the coastal shelf around the PEI and on the saddle separating the two islands, with maximum abundances previously recorded at depths between 50 and 100 m (Branch et al., 1993; Perissinotto and McQuaid, 1990). Despite detailed knowledge of the species’ biology and life history, it remains unknown whether the distribution of N. marionis is due to habitat, depth or food sources, and little to no in situ data exists on its habitat utilization or associations. Working within a sensitive marine protected area, we investigated these aspects using non-destructive benthic photography to relate directly the distribution and abundance of N. marionis to in situ physical and biological habitat characteristics. Knowledge of habitat usage and associations are important to 2

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differences in sessile epibenthic assemblages existed between stations that hosted N. marionis and those where it was absent (Pseudo-F = 63.58, Pperm < 0.001, d.f. = 1; Table 1), and among depth strata (Pseudo-F = 54.82, Pperm < 0.001, d.f. = 2). A significant interaction effect showed that the differences in epibenthic assemblages, between stations with a presence of N. marionis and those without, were dependent on the factor ‘Depth’ (Pseudo-F = 28.32, Pperm < 0.001, d.f. = 1; Table 1). All pairwise tests were significant, but tests involving the ‘Deep’ depth bin were not possible because N. marionis did not occur in the deep stations. SIMPER results comparing epibenthic assemblages between stations with and without N. marionis, showed that where the shrimp occurred, stations were characterised by greater abundances of bryozoans, red algae, polychaetes, sponges, hydroids and brachiopods, while stations where N. marionis was absent were distinguished by greater abundances of gorgonians and cerianthids (Fig. 3). Results of the SIMPROF cluster analysis identified four significantly different groups based on station-averaged epibenthic assemblage data (Fig. 4). These groupings are further referred to as biogenic habitat groups 1–4. When overlaid with presence/absence information for N. marionis, it was evident that distinct patterns of distribution of N. marionis relate to the biogenic habitat groupings. Biogenic habitat group 2 and group 3 did not host any N. marionis, while group 1 and group 4 largely consisted of stations where N. marionis was present. However, both groups 1 and 4 contained a single station at which no N. marionis was recorded. SIMPROF analysis indicated that in group 1, the single station without N. marionis (M5) had the most dissimilar (but not significantly so) epibenthic assemblages from the rest of the stations within the group (approximately 40% similar to the other stations), all of which hosted N. marionis. Substratum-type information overlaid onto the cluster dendrogram (Fig. 4) revealed that group 4 was the most homogenous, containing seven (87.5%) stations classified as mud, and only one (M4) as gravel. Group 1 contained two stations classified as mud, but the majority (66.7%) of the stations in group 1 had gravel substrata. Stations in groups 2 and 3 had diverse substratum types including rocky sand and rocky mud. N. marionis was only found at stations classified as either mud or gravel (groups 1 and 4), but was not necessarily detected at all mud or gravel stations. N. marionis was not found at stations classified as rocky mud or rocky sand. A SIMPER plot showing the characteristic species occurring in the biogenic habitat groups revealed that group 1 was characterised by a high abundance of red algae, while bryozoans were dominant in all other groups (Fig. 5). Bryozoan abundance was considerably greater in group 4 (N. marionis present) than in groups 2 or 3 (N. marionis absent). Sponges, polychaetes and brachiopods were more abundant in group 4 (bryozoan dominated) than in group 1 (red algae dominated). Testing the effects of these biogenic habitat groupings on the densities of N. marionis, results of the one-way PERMANOVA showed a significant effect (Pseudo-F = 90.55, Pperm < 0.001, d.f. = 3; Table 2). All pairwise tests among biogenic habitat groups were also significant (Pseudot 3.6–15.9, Pperm < 0.001; Table 2). As shown by the main PERMANOVA test's results, patterns of epibenthic assemblages were significantly affected by depth (Table 1). Likewise, a significant negative linear relationship existed between depth and transformed densities of N. marionis (Pearson's r23 = −0.69, p < 0.01). Although N. marionis was found at stations ranging from 50 to 160 m, their densities were greatest at depths less than 100 m. The maximum station-averaged density was 93.4 indiv/m2 at 90 m (M36). N. marionis was found at stations within the shallow and intermediate depth bins, but not at any deep stations (i.e. greater than 299 m). The only shallow station sampled where N. marionis was not found was station M5 at 60 m. The third SIMPER plot showing the characteristic species occurring in each depth strata revealed that shallow stations were characterised by the presence and high abundance of red algae, while bryozoans were dominant within the intermediate and deep depth strata (Fig. 6). Bryozoan abundance was fairly consistent across

2.2. Data treatment and analyses All data were analysed using PRIMER (Plymouth Routines in Multivariate Ecological Research, version 6.1.18, Clarke and Gorley, 2006) and PERMANOVA+ for PRIMER, version 1.0.8 (Anderson et al., 2008). Epibenthic percentage cover data were square-root transformed to down-weight the dominance of abundant epibenthic species, and a Bray–Curtis similarity matrix was generated. Multidimensional scaling (MDS) plots, based on sample-level and station-averaged epibenthic cover data, were used to visualize the presence/absence patterns of N. marionis in relation to epibenthic assemblages, and overall cover, respectively. For the station-averaged plot, data were overlaid with a scaled bubble plot representing the overall percentage bare substratum. A species vector overlay was used to depict the dominant underlying epibenthic species. Only vectors with a Spearman correlation measure > 0.4 were plotted. To test whether epibenthic assemblage composition differed among depth strata and between stations which hosted N. marionis and those that did not, a two-way semi-parametric permutation analysis of variance (PERMANOVA) was used. Type III sum of squares was employed with permutation of residuals under a reduced model. The factor “Depth bin” (Fixed, three levels) was crossed with the factor “Presence/Absence” of N. marionis (Fixed, two levels). Initially a main test was performed, followed by pair-wise tests if interactions were significant. Finally, a SIMPER analysis was done to determine which sessile epibenthic species were most influential in driving dissimilarity between stations that hosted N. marionis and those that did not. To further characterise patterns of epibenthic assemblages and substratum type, a hierarchical clustering with SIMPROF routine was done on station-averaged epibenthic cover data. This identified any significant grouping among stations based on the degree of similarity in epibenthic assemblages, and produced a cluster dendrogram which was overlaid with substratum-type and presence/absence information for N. marionis. For the purposes of our study these groupings of epibenthic assemblages are referred to as ‘biogenic habitat groups’. Using a second SIMPER analysis we identified the epibenthic species that contributed most to the respective biogenic habitat groups. Following this, a direct test of the effect of these biogenic habitat groups on densities of N. marionis was done using a one-way PERMANOVA with ‘Biogenic habitat type’ as a single fixed factor (equivalent to an F-test; Clarke and Gorley, 2006). The density data were square-root transformed to downweight the dominance of high densities, and then used to generate a Euclidean distance similarity matrix. A type III sum of squares was used, with an unrestricted permutation of raw data. This was followed by pair-wise tests among the four biogenic habitat groups. 3. Results Of the 27 stations sampled, eight were shallow, 11 intermediate and eight deep. Across the sampled depth range of 50–500 m, N. marionis was recorded between 62 and 160 m from 12 of the 27 stations sampled. A maximum density of 200 indiv/m2 was detected in the shallow depth bin in a single image, with the average density at this station being 93.4 indiv/m2. Estimates of percentage cover of sessile epibenthic assemblages ranged from 5% to 97%, and displayed a decreasing trend with depth. In the shallow depth bin, average cover was 70%, while average cover was 57% and 20% in the intermediate and deep depth bins respectively. The MDS plots showed a separation in epibenthic assemblage data that closely matched the superimposed categorization of the presence/ absence of N. marionis (Fig. 2a). The station-averaged MDS plot overlaid with the percentage bare substratum bubble plot showed that N. marionis was absent at stations where bare substratum was greater than 50% (mean = 75.1% ± SD 24.1; Fig. 2b). N. marionis were present at stations where the percentage of bare substratum was low (mean = 17.6% ± SD 12.5). PERMANOVA analysis confirmed that significant 3

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Fig. 2. a) Multi-Dimensional Scaling (MDS) plot representing Bray-Curtis similarity for sessile epifaunal cover data at stations inhabited by Nauticaris marionis (grey circle) and sites without N. marionis (open triangle); and b) MDS plot based on station-averaged epifaunal cover data with vector overlay. Bubble size represents the percentage bare substrate at each station, while bubble colour indicates presence (grey) or absence (white) of N. marionis. Table 1 Results of PERMANOVA testing differences in sessile epifaunal assemblages among sites where Nauticaris marionis was present and those where N. marionis was absent, across depth strata.

Main

Pairwise

Factor

df

SS

Nauticaris Depth bin Interaction N x D Res Total NxD Nauticaris Shallow Intermediate Deep Depth bin Absent

1 2 1 654 658 Groups

1.01E + 1.74E + 44,945 1.04E + 1.47E +

Present

MS

Pseudo-F

P (perm)

Unique perms

1.00E + 05 87,003 44,945 1587.2

63.582 54.815 28.317

0.0001 0.0001 0.0001

9951 9936 9953

t value

P (perm)

Unique perms

Presence/absence Presence/absence Presence/absence

6.394 8.519

0.0001 0.0001 No test possible

9943 9934

Shallow, Intermediate Intermediate, deep Shallow, deep Shallow, Intermediate Intermediate, deep Shallow, deep

5.871 4.99 6.563 10.785 No test possible No test possible

0.0001 0.0001 0.0001 0.0001

9950 9948 9954 9945

05 05 06 06

Fig. 3. SIMPER results showing the average abundances (square-root transformed; + SE) of the top eight distinguishing sessile epibenthic taxa contributing to dissimilarity of assemblages between stations hosting Nauticaris marionis and stations without N. marionis. The total percentage dissimilarity between these two groups is indicated in brackets, while contributions of individual taxa to dissimilarity are shown on the right-hand side. For each taxon, the group having the greater abundance is indicated by a black circular marker.

marionis was associated with structure-forming epibenthic cover at shallow and intermediate depths. The composition of epibenthic assemblages and depth significantly influenced the distribution and density of N. marionis. Associations with two distinct epibenthic assemblages were identified, one being shallow nearshore habitats dominated by red algae, the other being bryozoan-dominated habitats at intermediate depths located on the inter-island saddle. Although not explicitly tested due to a lack of sufficient replication of substratum types, our findings suggest that substratum type was a partial

all three depth strata. Two other structure-forming biota, polychaetes and sponges, were present within all three depth strata, however, were most abundant at intermediate stations. The deep depth category was characterised by low abundances of sponges and polychaetes, and the presence of gorgonians and cerianthids. 4. Discussion Our results show that at the sub-Antarctic Prince Edward Islands, N. 4

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Fig. 4. Dendrogram produced by cluster analysis with SIMPROF routine, based on station-averaged percentage cover data. Dashed branches indicate significantly different ‘biogenic habitat’ groups of epibenthic assemblages (1–4). For each station, the Presence/ Absence of Nauticaris marionis is indicated by either a tick (present) or cross (absent), and the lower symbols indicate the respective substratum type.

Fig. 6. Average abundances (+SE) from SIMPER analysis showing the top 5 taxa characteristic of each depth range. The average density (+SE) of Nauticaris marionis (indiv/ m2) is indicated above the groups which had populations of the shrimp.

based on photographic sampling done concurrently with the historical dredge work. This is comparable with the maximum mean density recorded in our study (ca. 93 indiv/m2). In contrast to the earlier studies however, we did not record N. marionis beyond 160 m, where previously they were found, albeit in low numbers (< 2 indiv/m2 in all cases), at around 390 m and even outside of our sampling range at more than 600 m (Perissinotto and McQuaid, 1990; Branch et al., 1993). Additionally, these previous local records indicate the presence of N. marionis on ‘rock’ substrata (Branch et al., 1993), while the only habitats we sampled that had at least partial rocky structure (‘rocky sand’ and ‘rocky mud’) hosted no N. marionis. These disparities may stem simply from the lack of sampling of true rocky habitat, but may also relate to differences in the sampling techniques used in the respective studies. Dredge sampling is potentially better at detecting (by direct collection) hidden individuals, but only provides an accumulation of habitat material and specimens from across an unknown number of habitat types or patches. It is also limited by the fact that density estimates are based on assumed duration of contact of the dredge with the substratum. In contrast, optical sampling may miss some cryptic individuals but is the only technique able to collect directly verified habitat-organism association data and, critically in our study, densities based on scaled sampling area (Williams et al., 2015). Another possible explanation for the absence below 160 m in our study is that N. marionis may exhibit seasonal variation in spatial or mobility patterns. This type of behaviour has been observed in the deep-sea shrimp Aristeus antennatus (Sardà et al., 1997). Comparisons to the distribution established by Branch et al., 1993 remain valid however, since sampling was carried out in the same season. In any case, previous abundances at these greater depths were low (< 2 indiv/m2), and our results emphasise that the primary distribution of N. marionis at the PEI extends from coastal

Fig. 5. Average abundances (+ SE) from SIMPER analysis showing the top 5 taxa characterising each of the biogenic habitat groups defined in the cluster analysis.

determinant of the distribution of N. marionis, as it predicted only where the species would not be found (rocky sand, rocky mud). In contrast, it was possible for areas of mud or gravel substrata to host N. marionis. Within these habitats, localised suitability seems to be determined by assemblage composition and the overall epifaunal cover provided. Broadly, the patterns of distribution and density of N. marionis at the PEI were similar to previous work, where peak densities were reached between 60 m and 90 m, declining with depth thereafter (Perissinotto and McQuaid, 1990; Branch et al., 1993). Density estimates of up to 25 indiv/m2 were described by Perissinotto and McQuaid (1990) based on dredge sampling at the islands, and closely match the peak density estimate of approximately 35 indiv/m2 recorded by Branch et al. (1993) at a depth of around 50 m. Interestingly, Perissinotto and McQuaid (1990) also cite a much greater peak density of 80 indiv/m2 at 61 m

Table 2 PERMANOVA results testing the effect of biogenic habitat groupings on the density of Nauticaris marionis. Main

Factor

df

SS

MS

Pseudo-F

P (perm)

Unique perms

3 605 608 Groups 4, 3 4, 2 4, 1 3, 1 2, 1

1229.9 2739.1 3969

409.98 4.5275

90.554

0.0001

9949

Pairwise

Bio habitat grps Res Total Bio habitat grps

t value 8.8883 8.2798 3.5978 15.901 14.811

P (perm) 0.0001 0.0001 0.0007 0.0001 0.0001

Unique perms 9836 9832 9822 9847 9845

5

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(Pakhomov et al., 2004; Richoux et al., 2016). Specifically, Richoux et al. (2016) identified differences in fatty acid signatures between nearshore (autotroph influenced) and deeper areas (heterotroph influenced). Compound-specific δ15N data indicated that the nearshore populations of N. marionis were 1st order carnivores while those in deeper inter-island areas were 2nd order (Pakhomov et al., 2004). Although these studies suggest that a common food source is an unlikely cause of the observed habitat associations, this does not preclude a scenario of generally enhanced food availability related to biogenic habitat. In theory, resource enhancement is certainly one aspect of facilitative interactions (Bruno et al., 2003). It has been shown that increased food availability in complex biogenic habitats, due to greater abundances of epiphytes and prey, can positively affect the densities of associating species, including predatory fish and decapod taxa (Bologna and Heck, 1999). The presence of N. marionis related to the threshold of total epibenthic cover (> 50%) in our study supports the view of habitat association driven by shared characteristics of epibenthic cover, including positive structural and resource effects, rather than characteristics of specific taxa. In the deep-sea, biogenic habitats provided by sponges, soft corals, sea fans and bryozoans are primarily used as refugia, particularly by crustaceans (Buhl-Mortensen and Mortensen, 2005; BuhlMortensen et al., 2010). This use of habitat structure can be especially influential on early survivorship. For crustacean taxa, the primary value of nursery habitat is derived from the provision of complex refugia (Loher and Armstrong, 2000). The availability of complex biogenic habitat is essential to the settlement and early post-settlement survival of juvenile crustaceans, (e.g. Loher and Armstrong, 2000, Pirtle and Stoner, 2010). As facilitation ecology shows, positive effects of biogenic habitat including environmental amelioration, enhanced recruitment, resource availability and refuge provision can expand the fundamental niche of a given organism to a larger ‘realised niche’ (Stachowicz, 2001; Bruno et al., 2003). It is likely that N. marionis benefits from multiple facilitative interactions with structure-forming epibenthos, particularly at intermediate depths where cover by bryozoan species clearly expands the shrimp's ecological niche beyond the extent provided by nearshore algal beds. This type of niche extention has the potential to be extensive, with records showing bryozoan-generated habitat for New Zealand and Antarctic regions extending to 800 m (Wood et al., 2012). Such associations with invertebrate fauna may be more influential than associations with substratum type (Pirtle and Stoner, 2010). For example, relative to substratum type, benthic macrofauna explained almost double (38%) the variation in spatial organisation of groundfishes in the Gulf of Lions (Gaertner et al., 1999). Moreover, associations with biogenic structure should be increasingly important in those deeper habitats that lack physical abiotic complexity. Although deep populations of N. marionis are definitely less abundant (even absent as in our sampling), N. marionis does form part of the diet of demersal (notothenioid) fishes (e.g. Blankley, 1982). This means that where the shrimp may occur beyond the reach of diving seabirds and seals, uptake by feeding fish may still mean that they fulfil their role as tophic link (sensu Perissinotto and McQuaid, 1990).

waters to at least around 160 m depth. This pattern is similar to that observed off the Otago peninsula, New Zealand, where N. marionis was recorded on mid-shelf habitats between 40 and 128 m, and in some outer-shelf areas up to 700 m depth (Probert et al., 1979). Substratum type shapes the physical structure of benthic habitats as well as the biotic characteristics, including epibenthic assemblage composition (Driscoll, 1967; Freeman and Rogers, 2003; Sahade et al., 2004; Laudien and Orchard, 2012). In our study, N. marionis was only found on mud and gravel substrata where substantial epibenthic cover also existed. This agrees with the data from the Otago peninsula, New Zealand, where N. marionis was recorded only on sandy-gravel substrata dominated by bryozoan epifauna (Probert et al., 1979). Confusingly, however, while Probert et al. (1979) note that red algae formed a dominant part of the ‘inshore sand’ habitats, the shrimp were not recorded as part of the ‘inshore’ assemblage. This is strange since our findings from the PEI and those of Branch et al. (1993), as well as results from Snares Islands, 200 km SW of New Zealand (Fenwick, 1978), all identify shallow inshore red algal habitats as having high densities of N. marionis. Although examination of historical data from PEI suggests an alignment of peak densities of the shrimp with inshore algal cover and total epibenthic cover (Branch et al., 1993), it does not show as clear an overlap between densities of N. marionis and bryozoan cover, as is highlighted in our results or those of Probert et al. (1979). The in situ habitat information provided by our photographic sampling resolves and refines the patterns suggested by Branch et al. (1993), identifying in detail two distinct epibenthic assemblages with which N. marionis associated. One assemblage was dominated primarily by red algae and the other by a high percentage cover of bryozoan species. As the interaction effect showed, differences in epibenthic assemblages among stations where N. marionis occurred and where it did not were dependent on depth. This result is not surprising since N. marionis is clearly associated with areas of substantial (> 50%) epibenthic cover and, as with our data, an inverse relationship between depth and benthic standing stock is well established (Rex et al., 2006). This suggests that only at depths where there is sufficient epibenthic cover will specific associations be observed. The association of N. marionis with two different biogenic habitat groups, each in different general locations relative to the islands, may be explained in two possible ways. One is that the association is driven by a feature common to both habitat groups. The obvious candidate here is the complex foliose or filamentous structure provided by both the red algae and bryozoan species (largely Cellaria malvinensis). Like the well-known relationships around seagrass, the importance of foliose red algae and complex bryozoans to faunal associations and biogenic habitat provision has been demonstrated in shallow and deep-sea habitats (Steller et al., 2003; Buhl-Mortensen et al., 2010; Wood et al., 2012). In the case of red algae, the number of organisms supported relate to structural characteristics such as branching density (complexity) and thallus volume (Steller et al., 2003). Similarly, in shelf and deep-sea habitats the abundance and diversity of organisms associated with biogenic habitats, such as soft corals and bryozoans, correlate with the complexity of host morphology (e.g. Klitgaard, 1996, BuhlMortensen et al., 2010). Several studies, including work on decapod crustaceans, point to associations with structure more than with specific taxa, even though different species may afford different degrees of shelter (Lewis, 1984; Heck et al., 2003; Stoner and Titgen, 2003). For example, research off Argentina recorded higher densities of decapods, including Nauticaris magellanica, in relation to Macrocystis pyrifera kelp forests and ‘other three dimensional structures’ (Barros et al., 2004). The second explanation is that habitat associations of shrimp may arise due to a common food source or food availability. Studies examining stable isotope and fatty acid signatures of N. marionis at the Prince Edward Islands, however, found that although the quality of food obtained by the shrimp was similar, their diet shifted according to their size (presumably ontogenetic change), location and depth

5. Conclusions Our study resolves and verifies the patterns of habitat use by N. marionis at PEI, most strictly, within austral autumn in which we sampled. This characterisation is an important record for a species that has been closely examined as an indicator of wider trophic and ecosystem change (Pakhomov et al., 2004, Allan et al. 2013). Identifying associations between species and habitat is relevant to understanding environmental influences on distributions, and although these interactions can be highly taxon specific, their net ecological effects may be far reaching (Gaertner et al., 1999; Bruno et al., 2003; Hughes et al., 2009). Our results indicate that N. marionis populations are strongly linked to 6

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