Spatial trends and environmental drivers of epibenthic shelf community structure across the

Item Type Thesis

Authors Bland, Aaron

Download date 30/09/2021 08:30:22

Link to Item http://hdl.handle.net/11122/10274 STRUCTURE ACROSS THE ALEUTIAN ISLANDS

By Aaron Bland, B.S.

A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Science in Marine Biology University of Fairbanks December 2018

APPROVED:

Brenda Konar, Committee Chair Katrin Iken, Committee Member Mark Johnson, Committee Member Mark Zimmermann, Committee Member Matthew Wooller, Chair Department of Marine Biology Bradley Moran, Dean College of Fisheries and Ocean Sciences Michael Castellini Dean of the Graduate School Abstract The continental shelf around the Aleutian Islands supports important commercial and subsistence fisheries as well as multiple seabird and marine mammal populations. To sustainably manage these populations, more information is needed on the distribution of the benthic communities that support some of the top level consumers. Given the vast size and highly variable physical environment of the Aleutian Islands, it is likely that epibenthic community structure on the continental shelf will vary by geographic area and physical and oceanographic conditions. This project examined spatial patterns in Aleutian epibenthic shelf communities among oceanographic regions (island groups separated by major oceanographic passes) and islands within these regions and identified environmental drivers responsible for important community divisions. Benthic trawls were conducted at 12 Aleutian islands across four oceanographic regions to characterize epibenthic shelf community structure along the island chain. It was tested whether the spatial variability in shelf community structure among regions and islands was correlated to multiple environmental variables including bottom water temperature, water depth, distance from shore, exposure, bottom rugosity, sediment grain size, sediment chlorophyll content, and drift algal food subsidies. Overall, communities differed both among regions and among islands within regions. Communities in the Far Western region (Near Strait to Buldir Strait) differed from communities in other regions, largely due to a high density of sand dollars in the Far West. However, none of the measured environmental characteristics explained this difference. Additionally, there was no evidence for a break in epibenthic shelf community structure across Samalga Pass between the East and the Central regions, even though Samalga represents a biogeographic break for many other Aleutian community types, including zooplankton, fish, and kelp forest communities. Within the Central region, a characteristic soft-sediment community (including the flatfish Atheresthes spp. and the crabs Labidochirus splendescens and Chionoecetes bairdi) distinguished from other Central islands. Compared with groundfish trawl surveys conducted by the Alaska Fisheries Science Center (AFSC), this study captured less fish but more invertebrates by biomass, which is likely related to different gear selectivity used by the two studies. These findings provide information on the distribution of Aleutian shelf communities that

i complement existing information from AFSC surveys. In particular, it is shown that there is potentially an important division in epibenthic shelf communities across Buldir Strait, in agreement with the literature identifying this pass as an important biogeographic break. Furthermore, it is suggested that future assessments of Aleutian epibenthic communities should employ a combination of sampling gear types to better represent various epibenthic taxa.

ii Table of Contents

Abstract ...... i Table of Contents ...... iii List of Figures ...... iv List of Tables ...... v Introduction ...... 1 Methods ...... 7 Study region ...... 7 Epibenthic trawls ...... 8 Environmental drivers...... 10 Alaska Fisheries Science Center bottom trawls ...... 12 Region definitions ...... 13 Data analysis ...... 13 Results ...... 15 Spatial organization of epibenthic shelf communities ...... 15 Environmental drivers...... 17 AFSC trawl survey comparisons ...... 19 Discussion...... 19 Summary ...... 27 Works Cited...... 28 Figures and Tables ...... 43

iii List of Figures Figure 1. Map of the Aleutian Islands displaying major ocean currents (top panel), depths of oceanographic passes (middle panel), and island locations (bottom panel)...... 44 Figure 2. Map of the Aleutian Islands indicating the islands sampled...... 45

Figure 3. Bar plot of average island total epibenthic shelf biomass...... 47 Figure 4. Bar plot of average island total epibenthic shelf abundance...... 48 Figure 5. Bar plot of average island epibenthic shelf taxon richness...... 49 Figure 6. Map of trawl locations displaying the relative biomass of the ten taxa that best represented epibenthic community structure in terms of biomass (BVSTEP Primer-e, p = 0.857), separated by region...... 54 Figure 7. Map of trawl locations displaying the relative abundance of the seven taxa that best represented epibenthic community structure in terms of abundance (BVSTEP Primer-e, p = 0.855), separated by region...... 55 Figure 8. Average island biomass CPUE for the three epibenthic shelf taxa that best distinguish the Far West from the other regions...... 56 Figure 9. Average island biomass CPUE for the three epibenthic shelf taxa that best distinguish Adak Island from other islands in the Central region...... 57 Figure 10. Plot of trawl bottom temperatures from the present study and the AFSC trawl surveys (2010-2016) versus Arc Distance...... 58 Figure 11. Box plot of bottom temperatures for each region...... 59 Figure 12. Box plots of site-level exposure, sediment grain size (Φ), and bottom water temperature for the islands in the Central region...... 62

Figure 13. Map of trawl locations at Adak Island (diamonds; n = 6 total from both years) and Station ADKA2 (Adak Island) of the NOAA National Data Buoy Center (square)...... 62

Figure 14. Comparison of average total CPUE, fish CPUE, and invertebrate CPUE for trawls from the AFSC trawl surveys (2014 and 2016) for sites on the continental shelf (< 200 m, n = 262) and the present study (n = 39)...... 63

iv List of Tables Table 1. List of trawl site information, including the sampling year, the island and region in which the trawl was conducted, the GPS coordinates of the trawl midpoint location (decimal degrees), the arc distance (kilometers), the average trawl depth (meters) and the midpoint distance to shore (meters)...... 45 Table 2. PERMANOVA pairwise comparisons of shelf community structure among regions by biomass...... 49 Table 3. PERMANOVA pairwise comparisons of shelf community structure among islands within each region by biomass...... 51 Table 4. PERMANOVA pairwise comparisons of shelf community structure among regions by abundance...... 52 Table 5. PERMANOVA pairwise comparisons of shelf community structure among islands within each region by abundance...... 53

v Introduction The Aleutian Islands are a 1900 km chain of islands that extends from the Alaska Peninsula, USA to the near the Kamchatka Peninsula, Russia (Figure 2). These islands have considerable economic, cultural, and ecological importance. The Aleutians provide for substantial commercial fisheries with total landings exceeding 80,000 metric tons in 2018 through September 8th ( Aleutian Islands Catch Report (includes CDQ), 2018). Subsistence fisheries support the economy and culture of the resident Unangan/Unganax (or Aleut) communities (Davis, 2005). The Aleutian Islands are also important habitat for seabirds and marine mammals. Twenty-six breeding species of seabirds inhabit the Aleutians in numbers exceeding 10 million individuals (USFWS, 2000). Aleutian sea otters (Enhydra lutris) were hunted to near extinction in the eighteenth and nineteenth centuries (Kenyon, 1969), but recovered to a peak population of 55,000-74,000 individuals in the mid 1980s (Estes, 1990). The Stellar sea lion (Eumetopias jubatus) also inhabited the Aleutians in high densities (Kenyon and Rice, 1961), with an estimated 245,000-290,000 individuals in the Bering Sea/Aleutian region in 1980 (Loughlin et al., 1984). However, multiple Aleutian bird and marine mammal populations experienced precipitous population declines in the mid to late 20th century (Braham et al., 1980; Byrd and Williams, 2004; Estes et al., 2005). There have been many investigations into the causes of the declines (Springer, 1992; Springer et al., 2003; Trites et al., 2007; Trites and Donnelly, 2003), which have greatly improved understanding of Aleutian ecology. However, in the interest of improving the sustainable management of Aleutian animal populations and fishery resources, multiple calls have been put forth for additional research on the organization and distribution of Aleutian biological communities (Aydin et al., 2007a; Schumacher and Kruse, 2005). Several Aleutian biological communities have spatial variability that corresponds to spatial variability in physical conditions, as illustrated at Samalga Pass (Coyle, 2005; Heifetz et al., 2005; Konar et al., 2017; Logerwell et al., 2005; Sinclair and Zeppelin, 2002). Here, the zooplankton community switched from neritic taxa in passes east of Samalga to oceanic taxa west of Samalga (Coyle, 2005). Changes in water temperature and salinity accounted for up to 50% of this observed variability (Coyle, 2005). In addition, the structure of macroalgal,

1 invertebrate, and fish communities inhabiting kelp forests differed on either side of Samalga Pass (Konar et al., 2017). Given that multiple Aleutian communities have important ecological differences across Samalga Pass, Samalga is widely considered to be an important biogeographic break (Hunt and Stabeno, 2005; Konar et al., 2017), defined here as an area across which there are conspicuous differences in community structure that may represent the range limits for multiple taxa. While many of these Aleutian biogeographical patterns align well with current understanding of Aleutian oceanography and geography, the mechanisms underlying the biogeographic relationships are rarely demonstrated (Heifetz et al., 2005; Konar et al., 2017; Logerwell et al., 2005; Springer et al., 1996; but see Coyle, 2005). As more information is made available regarding the organization of different types of Aleutian biological communities, additional biogeographic patterns may be discovered. Epibenthic communities are one of the more ecologically and economically important biological community types in the Aleutians. These communities include a myriad of taxa representing several invertebrate phyla including sponges, bryozoans, echinoderms (such as sea stars, brittle stars, sea urchins, and sand dollars), arthropods (such as crabs, shrimps, and benthic amphipods), mollusks (such as bivalves, gastropods, and cephalopods), cnidarians (such as corals, anemones, and hydroids), annelids, and others (von Szalay et al., 2017). In addition to the invertebrates, these communities include many groundfish. The most abundant groundfish species found in recent Aleutian bottom surveys include Pacific Ocean perch (Sebastes alutus), Atka mackerel (Pleurogrammus monopterygius) and northern rockfish (Sebastes polyspinis) (Raring et al., 2016; von Szalay et al., 2017). Other typical groundfish include flatfish, such as arrowtooth flounder (Atheresthes stomias) and northern rock sole (Lepidopsetta polyxystra), and skates (Raring et al., 2016; von Szalay et al., 2017). One of the most important functions of benthic communities in general is to consume and recycle carbon and nutrients that settle out of the water column (Grebmeier and McRoy, 1989; Renaud et al., 2007). Deposit-feeding benthic organisms consume plankton, particulate organic matter, plant detritus, diatoms, and bacteria that are deposited on the bottom and may be unavailable to pelagic-feeding organisms (Aydin et al., 2007b; Levinton, 1972). Another important function of benthic communities is to support higher trophic levels. Benthic invertebrates and fishes make up significant proportions

2 of the stomach contents of several Aleutian fishes (Aydin et al., 2007b; Logerwell et al., 2005; Yang, 2000). Aleutian benthic organisms are also preyed upon directly by multiple bird taxa (Springer et al., 1996) and marine mammals, including sea otters (Kenyon, 1969) and Steller sea lions (Sinclair and Zeppelin, 2002). Finally, Aleutian groundfish and shellfish feed humans through commercial (Aydin et al., 2014) and subsistence (Davis, 2005) fisheries. In addition, some Aleutian epibenthic invertebrates, particularly corals and sponges, provide important habitat for fish and other invertebrates (Freese et al., 1999; Krieger and Wing, 2002). Although some information is known about the makeup and distribution of Aleutian epibenthic communities, many questions remain regarding its spatial differences and the drivers of this variability. As found in other epibenthic communities, the Aleutians may be organized at regional scales (> 100s km) in association with large-scale, oceanographic features, such as water masses (Callaway et al., 2002; Pires, 1992; Stewart et al., 1985). Epibenthic communities can also vary at smaller scales (10s km) in association with variable local-scale habitat features including seabed characteristics (Sanchez et al., 2008; Williams et al., 2010) and hydrodynamic regimes (Archambault and Bourget, 1999). Given the economic and ecological importance of epibenthic communities, the National Marine Fisheries Service (NMFS) has conducted extensive epibenthic surveys in the Aleutians. The Resource Assessment and Conservation Engineering (RACE) Division of the Alaska Fisheries Science Center (AFSC) within NMFS has conducted 14 comprehensive bottom trawl surveys of the Aleutian contintental shelf and slope (< 500 m depth) since 1980 (von Szalay et al., 2017). These surveys provide important information for assessments of Aleutian demersal fish stocks as part of multiple fishery management plans (Aydin et al., 2014). Furthermore, these data have been used to evaluate biogeographic trends for Aleutian fish (Logerwell et al., 2005) and coral (Heifetz, 2002; Heifetz et al., 2005) communities. Important findings of these surveys included the discovery that the demersal fish community differed in species richness, distribution, and diet across Samalga Pass (Logerwell et al., 2005). Additionally, two distinct rockfish community types were mostly separated by Pass, and west of Buldir Strait, species richness declined and walleye pollock catches were lower than to the east (Logerwell et al., 2005). Furthermore, the diversity of cold-water corals increased to the west of Samalga Pass (Heifetz

3 et al., 2005). In addition to the bottom trawl surveys, the NMFS conducted underwater camera surveys in 2012 and 2014 (Goddard et al., 2017) that were used to validate models of the distribution of Aleutian deep-sea corals and sponges (Rooper et al., 2018). The surveys also were used to evaluate the effects of substrate, currents, depth, and fishing pressure on Aleutian cold-water coral and sponge communities (Wilborn et al., 2018). Together, the AFSC bottom trawl and NMFS camera surveys have provided important benchmark information on Aleutian epibenthic community structure. While much knowledge has been gained from the AFSC/NMFS surveys, there are still important gaps of information regarding Aleutian epibenthic communities. The objectives of the AFSC trawl surveys and NMFS camera surveys were primarily to provide information on commerically and ecologically important groundfish and invertebrate taxa (Goddard et al., 2017; von Szalay et al., 2017). As a consequence, the quality and specificity of field identification for some non-commercial taxa has fluctuated over the years (Orr et al., 2014). Similarly, images collected from the NMFS camera surveys were only analyzed to quantify densities of fishes, crabs, and structure-forming invertebrates (e.g., corals, sponges, sea pens) (Goddard et al., 2017). Prioritizing commercially important fish and invertebrates is a necessary effort-saving measure that permits the trawl and camera surveys to extensively sample the Aleutian continental shelf and slope in a single sampling season. However, this prioritization comes with a significant trade-off: information on many Aleutian epibenthic invertebrate taxa is either missing or limited (Orr et al., 2014), resulting in a potentially biased understanding of the structure of Aleutian epibenthic communities. Although many of these taxa may have limited direct commercial value, they contribute to the overall functioning of shelf communities (Aydin et al., 2007b). Therefore, there is a pressing need to re-evaluate the structure of Aleutian epibenthic communities in a more comprehensive manner. In many shelf systems, distinct epibenthic communities are associated with differing water masses because water masses can characterize the physical environment in which epibenthic communities develop (Thorson, 1957). For instance, the epibenthic community of the North Sea is divided into two community types: the southern community is dominated by free-living species, while the northern community is typified by sessile species (Callaway et al.,

4 2002). The northern community occurs in thermally stratified waters with low seasonal fluctuation in bottom temperature, while the southern community experiences vertically mixed waters with greater fluctuation in bottom temperature (Callaway et al., 2002). The epibenthic communities on the shelf of Ubatuba, southeastern Brazil, also separate by water masses of differing temperatures (Pires, 1992). Species tolerant to low temperatures were more common on the northern shelf, while tropical species were more abundant on the central and southern inner shelf (Pires, 1992). Meanwhile, the epibenthic communities of the Chukchi Sea are divided between the southeast and northeast (Feder et al., 2007). With the influence of Alaska Coastal Water, the southeastern Chukchi experiences more complex water mass and flow patterns than the northeastern Chukchi (Feder et al., 2007). The flow patterns of the southeastern Chukchi widely disperse particulate organic carbon and support a more productive benthic community (Feder et al., 2007). Various aspects of bathymetry and topography can also influence the structure of epibenthic communities including depth, bathymetric heterogeneity, and exposure. In many systems, the abundance, biomass, and diversity of epibenthic organisms decrease with increasing depth (Cohen et al., 2000; Wei et al., 2010). Reductions in macrofaunal size and abundance with depth are related to the decreased delivery of organic carbon to epibenthic communities at depth (Darnaude et al., 2004; Rex et al., 2006). Epibenthic communities living in shallow water may be strongly affected by environmental forcing originating at the sea surface, such as disturbance via storm events, coastal erosion, and ice scour (Conlan et al., 2008). Bathymetric heterogeneity can structure epibenthic communities on multiple spatial scales. While much attention has been given to the effects of small-scale (1-100 mm) habitat heterogeneity (Bourget et al., 1994; Lapointe and Bourget, 1999; Lemire and Bourget, 1996), bottom rugosity can also affect epibenthic species richness at a larger spatial scale (1 km) (Archambault and Bourget, 1996). Finally, the degree of exposure to oceanic hydrodynamics affects water motion at the benthos and can influence epibenthic communities. In the St. Lawrence Estuary, Canada, the diversity, percent cover, and recruitment of benthic organisms was greater inside of bays where larvae are likely retained longer than along the outer shore (Archambault and Bourget, 1999).

5 Epibenthic communities also can be structured by various sediment properties where different epibenthic taxa are expected to occur on sediment of differing grain size. For example, sessile taxa require coarse sediment or bedrock to settle on, and are less likely to occur on muddy bottoms (Bluhm et al., 2009; Rees et al., 1999). Furthermore, depth and sediment grain size can be correlates of hydrodynamic energy and available organic material such that fine grained sediment only occurs in low-energy environments (Snelgrove and Butman, 1979). High current flow is particularly important for sessile suspension feeders that depend on currents to deliver food (Leichter and Witman, 1997; Pisareva et al., 2015). Therefore, differences in sediment grain size may relate to various epibenthic community types by indirectly indicating long-term hydrodynamical processes (Bergen et al., 2001; Snelgrove and Butman, 1979). Finally, the input of carbon to the benthos has the potential to shape epibenthic communities. Sites that are far from shore receive less terrestrially-derived carbon and nutrients compared to sites closer to shore, and, therefore, epibenthic productivity may be lower (Gallo et al., 2015; Lapointe et al., 1994) such that distance from shore can be important independent of depth. Sediment chlorophyll content reflects accumulations of both fresh phytodetritus and chlorophyll-containing fecal pellets and, therefore, the input of pelagic- derived primary and some secondary production to the benthic environment (Graf, 1989). This food availability has the potential to determine benthic biomass (Grebmeier et al., 1988) and drive differences in epibenthic size frequency distributions (Konar et al., 2014). Another potentially important source of carbon delivered to some offshore epibenthic communities is kelp detritus advected from the nearshore. Kelp produces detritus through blade erosion and fragmentation and the dislodgement of whole fronds from storm events (Krumhansl and Scheibling, 2012). Epibenthic organisms with access to these drift algal subsidies are more productive than those without this valuable food input (Kelly et al., 2012; Vetter, 1995). This research addresses a knowledge gap for the Aleutian Islands ecosystem by describing and interpreting spatial variability in Aleutian epibenthic shelf community structure. As such, the first objective was to investigate whether Aleutian epibenthic shelf communities vary among oceanographic regions and among islands within those regions. The second objective of this project was to identify environmental drivers that best explain the observed

6 patterns in epibenthic community structure. A third objective of this project was to compare its key findings with the findings of the publicly-available dataset generated by the AFSC Aleutian bottom trawl surveys. The purpose of this comparison was to highlight important differences in the sampling effectiveness of the AFSC trawl protocols versus the present study and provide context for the respective survey results.

Methods Study region The continental shelf and oceanographic environment surrounding the Aleutian Islands are variable. The width of the continental shelf is the greatest in the eastern Aleutians (from the Alaska Peninsula to Samalga Pass, Figure 1) and narrows towards the central Aleutians (Samalga Pass to Amchitka Pass; Stabeno et al., 2005). The Rat Island group (Amchitka Pass to Buldir Strait) is comprised of relatively small islands on a narrow shelf, but the shelf at the (Buldir Strait to Near Pass) is comparatively broad and shallow (Hunt and Stabeno, 2005). The oceanic passes that run between the islands facilitate the exchange of water between the North Pacific Ocean and the Bering Sea (Stabeno et al., 2005; Figure 1). The passes vary considerably in depth (165-1155 m) and area (1-46 km2; Hunt & Stabeno, 2005; Figure 1). Consequently, passes at various points along the island chain differ in net flow rate and mixing depth, affecting the transport of nutrients to the Bering Sea (Stabeno et al., 2005). The water flowing through the passes and around the islands are sourced from three major ocean currents (Figure 2). The Alaska Coastal Current (ACC) originates in the Gulf of Alaska by a combination of wind forcing and freshwater discharge (Reed, 1987; Schumacher and Reed, 1980; Stabeno et al., 2004). The ACC flows along the Pacific side of the eastern Aleutian Islands, diverting into the Bering Sea from False Pass to Samalga Pass (Ladd et al., 2005; Stabeno et al., 2004). The Alaska Stream (AS) is a narrow, high-speed, western boundary current of the North Pacific sub-arctic gyre (Reed, 1984; Thomson, 1972). The AS flows westward along the Aleutian shelf break, providing Bering Sea inflow from Samalga Pass to Near Strait (Ladd et al., 2005; Reed and Stabeno, 1993). At Amchitka Pass, the AS breaks away from the continental slope as the island chain arcs northward. Therefore, the AS tends to form

7 meanders and eddies in the western Aleutians (Stabeno and Reed, 1994; Thomson, 1972). Compared to the ACC, the AS is relatively cool, saline, and nutrient rich, resulting in an oceanographic front at Samalga Pass (Ladd et al., 2005). Furthermore, the relatively deep passes to the west of Samalga Pass promote deep mixing, bringing nutrients at depth to the surface while simultaneously mixing phytoplankton below the photic zone (Mordy et al., 2005). For this reason, nutrient levels are higher to the west of Samalga Pass but primary production is lower (Mordy et al., 2005). Finally, the Aleutian North Slope Current (ANSC) is formed on the Bering Side of the islands by the AS flowing north through various Aleutian passes, especially Amchitka Pass (Chen and Firing, 2006; Stabeno and Reed, 1994). The ANSC flows along the Bering side of the islands from Amchitka Pass eastward (Reed and Stabeno, 1999; Stabeno and Reed, 1994). The ANSC also has a front at Samalga Pass where it becomes warmer, fresher, and more nutrient poor to the east, due to the influence of the ACC (Ladd et al., 2005). The climate throughout the Aleutians is considered maritime; cool, wet, windy, and foggy (Rodionov et al., 2005). However, there is likely a split in the long-term climate between the western and eastern Aleutians (Rodionov et al., 2005). The Aleutians east of around 170° W (near Samalga Pass) shifted to a warmer climate in 1977, but the western Aleutians have steadily cooled since the 1950s (Rodionov et al., 2005). Furthermore, during the Medieval Warm Period (900-1350 AD), temperatures were relatively low in the eastern Aleutians and Gulf of Alaska but were warm at Bering and islands in the west (Causey et al., 2005). Given the variability in the dimensions of oceanic passes, shelf bathymetry, and water mass properties, plus a long-standing split in climate, the Aleutian Islands are a region of high spatial variability in physical conditions.

Epibenthic trawls Aleutian epibenthic shelf community data were collected on two cruises in the Aleutian Islands in June 2016 and July 2017 aboard the R/V Oceanus. Benthic tows were conducted on level bathymetry on the continental shelf (< 200 m depth) at approximately 1-5 km away from historic nearshore monitoring sites (Estes and Duggins, 1995; Figure 2). Three trawls were attempted at each island; however, the lack of suitable trawl sites occasionally limited the number of trawls at an island (Table 1). Trawl sites were separated by at least 1 km, with a

8 maximum span of 18 km over an island's shelf, but more frequently the extent was around 4-8 km. Furthermore, trawl sites were generally located on the Bering side of the islands. Flat bathymetry was targeted to increase the chance of trawling over a soft-sediment benthos, thereby minimizing potential damage to the trawl net as well as standardizing the substrate type for community comparisons. When possible, sites were selected such that trawl depths varied at an island. This was done so that differences in shelf community structure among islands would not be confounded by differences in sampling depth at different islands. In addition, because the eastern and some of the central islands were sampled in 2016 and the western and other central islands were sampled in 2017, trawl comparisons may be confounded by potential interannual variability. To determine whether interannual variability in epibenthic shelf community structure was significant between the two years, five trawl sites from the 2016 cruise at Adak and Atka islands were revisited in 2017. At each site a 3.05 m plumb staff beam trawl with a 7-mm mesh and a 4-mm codend liner (Gunderson and Ellis, 1986) was towed for approximately three minutes on the seafloor with the vessel travelling at 1.5 knots. A temperature-depth recorder (ReefNet Sensus Ultra) was attached to the trawl net to determine effective trawling distances and average water temperature and depth for each tow. The start of each tow was determined as the time at which the trawl net stopped descending in the depth profile, and the end of each tow was determined as the time the trawl net began ascending. Trawl distances were determined by referencing the GPS coordinates of the research vessel for the start and end times of each trawl event. Occasionally, the trawl net was damaged or obstructed by rocks during a tow, which bent the plumb staff beam (Table 1). For these trawls, the collision point was detectable by a sudden decrease in depth of the trawl net, and the effective trawling swath was assumed to be from the beginning of the trawl up to the collision point. This would mean that catch per unit effort (CPUE) values are overestimated for any epibenthic taxa that were sampled after the collision point. However, this was determined to be preferable to underestimating epibenthic CPUE by assuming the trawl net was effectively sampling post-collision. Organisms from the catch were sorted and identified to the lowest taxonomic level feasible and weighed for damp­ biomass (including shells for hermit crabs) using hanging spring scales with accuracy to the

9 nearest 0.05 kg. Taxa that occur as discrete individuals (not colonial) were counted. All algae caught by the trawl net were assumed to be drift from the nearshore and were excluded from the epibenthic community dataset but were used as an environmental driver of benthic community structure (see below). To address potential interannual variability, variability in shelf community structure between both sampling years was quantified for Adak and Atka islands, which were visited in both years. A Bray-Curtis resemblance matrix by biomass was generated for the eleven trawl samples from both years from Adak and Atka. A PERMANOVA was run on this resemblance matrix using Island and Year as factors. Island explained a significant amount of variation in epibenthic shelf community structure, but Year marginally did not (Island: Pseudo-F = 3.66, p = 0.012; Year: Pseudo-F = 1.72, p = 0.052). Furthermore, the estimated component of variation explained by the Island factor (26.9%) was greater than the variation explained by the Year factor (7.3%). Furthermore, both components had considerably lower explanatory power than the residual variation (53.9%). Therefore, it was concluded that interannual variation in community structure was likely relatively minor compared to among-island variability and other untested variables, so interannual effects were no longer considered for all subsequent analyses.

Environmental drivers The environmental variables investigated were arc distance, bottom water temperature, depth, distance to shore, rugosity, exposure, sediment grain size and chlorophyll content, and total drift algal biomass. An “arc distance” was determined for each trawl site to provide a univariate measure of spatial relationships among trawl locations. A 4-n polynomial was fitted to trawl locations using the polyfit function in Matlab 9.2 R2017a, providing a “curve of best fit” for the trawl sampling locations. The curve was then imported into ArcMap, and for each trawl, the nearest point along the fitted curve was determined. The distance along the curve to reach these fitted points was assigned as the arc distance for each respective trawl, with the trawl the farthest west (trawl 29 at Attu) assigned a value of 0 m and increasing values eastward. Bottom water temperature and depth for each trawl were determined using the temperature-depth recorders attached to the trawl net. The water temperature and depth

10 data, which were recorded at 10 second intervals, were averaged over the duration the trawl net was in contact with the bottom. Additional bathymetric and geographic environmental variables were determined for each trawl location using ArcMap 10.4. For each tow, distance to the shore was determined by calculating the nearest distance between the trawl midpoint location and shore. The shoreline was the Alaska Coast 1,000,000 coastline provided by the Alaska Department of Natural Resources AK State Geo-Spatial Data Clearinghouse (http://www.asgdc.state.ak.us/). Trawl site rugosity (bathymetric surface area divided by planimetric surface area) was determined using the 100-m smooth sheet bathymetric raster provided by the AFSC (Zimmermann et al., 2013) and the DEM (Digital Elevation Model) Surface Tools extension for ArcMap (Jeness, 2013). The bathymetric raster was converted to a raster of surface area ratios using the DEM Surface Tools “Surface Area and Ratio” function. The surface area ratio was determined for each tow by averaging values within 500 m of each trawl midpoint location. Finally, an index of exposure (or fetch) was calculated for each tow by drawing 36 lines radiating from each trawl midpoint location at 10° intervals. The exposure for each site was calculated as the fraction of lines that did not intersect with a shoreline out of all 36 lines. Exposure was calculated separately for lines 5 km long and 10 km long. To quantify bottom sediment grain size and chlorophyll content at trawl locations, bottom sediment was collected prior to each trawl during the 2017 cruise only with a 0.1 m2 van Veen grab. For sediment chlorophyll a analysis, a random subsample of the top 2 cm of the grab was collected with a 2.8 cm diameter syringe barrel and stored in whirl packs wrapped in aluminum foil. This sediment was kept at -40 °C until it could be further processed (approximately four months later) in the laboratory. Chlorophyll was extracted from sediment with 100% acetone, and the fluorescence of the resulting supernatant was determined using a fluorometer (Turner Designs TD-700; Arar and Collins, 1997). After extraction, sediment samples were dried at 60 °C until there was no detectable change in weight due to water loss (on average 108 hours), and chlorophyll concentration per gram of dry sediment was determined. For sediment grain size, a random subsample of the top 5 cm of sediment was collected and stored in whirl packs at room temperature. Grain size analysis was conducted

11 using standard protocols (Folk, 1980). From each sample, 15-45 g of sediment was rinsed through sieves (2 mm and 63 μm with water. Sediment retained on the sieves and in the flow­ through were then dried at 90 °C for 24 hours. After drying, sediment retained on the 63 μm sieve was sieved (1 mm, 500 μm, 250 μm, 125 μm, and 63 μm) without water. Small quantities of 30% hydrogen peroxide were added to the silt/clay component of the sediment to remove any remaining organic content. The relative weights of various size-fractions of the sediment retained on each sieve were used to calculate phi (φ) values (Krumbein, 1936) as a measure of sediment grain size for each sediment sample. The algal drift available at each trawl site was estimated as a potential nearshore food subsidy to offshore epibenthic shelf communities. This was determined from the total biomass CPUE of drift algae caught in each trawl.

Alaska Fisheries Science Center bottom trawls AFSC Aleutian Groundfish survey data were analyzed for multiple comparisons with this study (https://www.afsc.noaa.gov/RACE/groundfish/survey data/data.htm). AFSC trawls surveyed more than 400 locations for each of 14 sampling years since 1980 using a high- opening Poly Nor'Eastern bottom trawl with bobbin-style roller gear (Stauffer, 2004). Trawl sites ranged from nearshore locations to 500 m depth, and tows were generally conducted for approximately 15 minutes of bottom contact (von Szalay et al., 2017). Only trawls conducted on the continental shelf (< 200 m) were used for comparative analyses. Trawl sites from the AFSC trawl surveys were assigned an Arc Distance by determining their fitted locations along the same curve generated for the present study. To determine whether bottom water temperatures measured in the present study were representative of the longer-term temperature environment, bottom water temperatures from this study and the AFSC surveys (taken from loggers attached to the AFSC trawl nets) from the last decade (2006-2016) were plotted against arc distance. A two-way ANOVA (anovan in MATLAB) was performed on the bottom temperature data with region (see below) and survey as grouping factors. Epibenthic shelf community comparisons were performed with the two most recent AFSC surveys (2014 and 2016) to minimize temporal effects. Specifically, total biomass CPUE, total fish biomass

12 CPUE, and total invertebrate biomass CPUE were compared between the AFSC data set and the present study.

Region definitions For this study, regional variation was examined by separating the Aleutian continental shelf into four a priori regions (Far West, West, Central, and East; Figure 1). These regions were delineated by three important oceanographic passes: Buldir Strait (depth: 640 m; cross­ sectional area: 28.0 km2) separates the Far West (Near Islands) from the West (); Amchitka Pass (depth: 1155 m; cross-sectional area: 45.7 km2) separates the West and Central regions; and Samalga Pass (depth: 200 m; cross-sectional area: 3.9 km2) separates the Central and East regions.

Data analysis Univariate community analyses were performed using MATLAB R2017a (Mathworks, Natick, Massachusetts, USA) and multivariate community analyses were performed using PRIMER v7 (Clarke and Gorley, 2015). Biomass and abundance data for each trawl were calculated as CPUE by dividing the weights and counts for each haul by the estimated trawl swath area (estimated trawl swath multiplied by 2.26 m effective trawling width; Gunderson and Ellis, 1986). Biomass and abundance CPUE were fourth-root transformed to downweigh the relative importance of the most abundant taxonomic groups. Similarities in epibenthic community structure among trawl sites were calculated using Bray-Curtis resemblance matrices for both biomass and abundance data. Significance level in all statistical analyses was set at a = 0.05. Aleutian epibenthic shelf communities were examined for differences among regions and islands within regions in terms of total biomass, total abundance, taxa richness with two­ way ANOVAs (anovan function in MATLAB) using the factors Region and Island nested within Region. When the global ANOVA identified significant differences, pairwise comparisons were performed (multcompare function in MATLAB) to determine which regions, and which islands within regions, differed. To determine whether differences existed in shelf community structure among regions and islands within regions, a PERMANOVA (Primer-e) was performed on the trawl sample

13 resemblance matrix using the factors Region and Island nested within Region. When the global PERMANOVA test indicated differences in community structure, pairwise PERMANOVA tests were performed to determine which regions, and which islands within regions, differed. For pairwise comparisons, significant differences between pairs of islands and regions were evaluated using Monte-Carlo P values. These values provide a more robust interpretation of significance when few samples among the pair of factors are examined and, therefore, limited unique permutations of the multivariate dataset are possible. To generate a reduced list of taxa that strongly correlates with the resemblance patterns of the full community data, the BEST (BVSTEP) routine was performed on both the biomass and abundance data with a stopping criterion of p > 0.85. SIMPER analyses were used to identify taxa that typify regions or islands that significantly differed from other locations. Taxa that together contributed 70% of each within-group similarity or distinguished regions or islands were determined in this manner. The environmental variables investigated were arc distance, bottom water temperature, depth, distance to shore, rugosity, exposure (5 km and 10 km), sediment grain size and chlorophyll content (2017 only), and total drift algal biomass. Rugosity, sediment chlorophyll a, and total drift algal biomass data were log-transformed to ensure an even spread in values. All abiotic variables were normalized (Primer-e). The environmental drivers were examined for high intercorrelations (p > 0.80). Sediment chlorophyll content was correlated to sediment grain size after transformation (p = 0.88), so sediment chlorophyll was excluded from analysis. Additionally, exposure at 5 km was correlated to exposure at 10 km (p = 0.90), so exposure at 5 km was excluded from analysis. To determine which combination of environmental drivers best explain multivariate patterns in epibenthic shelf community structure, the BEST (Bio-Env, Primer-e) routine was run on the fourth-root transformed shelf biomass and abundance data with the environmental variables as the explanatory data set. The BEST routine was run on all sites from both years but it excluded sediment data. In addition, the analyses were repeated for only the sites visited in 2017 for which sediment data existed (except tow 29 at Attu (Table 1). Environmental drivers identified as significant by Bio-Env analyses were examined for differences among oceanographic regions and among islands within regions using ANOVA. Significant regions or islands within regions were identified using the Tukey's honestly

14 significant difference procedure. Given that arc distance was used as a proxy for established spatial relationships among epibenthic shelf communities, it was not examined with ANOVA tests even when it was identified as an important driver. Very fine sediment was collected at Adak. One possible reason for this fine sediment is that winds predominantly come over the land at Adak before arriving to the trawl sites, and, therefore, the influence of wind-driven currents on bottom conditions is limited, promoting the deposition of fine grained sediment. To examine this possibility, wind speed data for Adak were taken from the NOAA National Data Buoy Center (http://www.ndbc.noaa.gov/; Station ADKA2 Adak Island: 51.861N 176.637W) and a wind rose was generated. Data were only used from years for which recordings occurred in each month (2006-08 and 2010-17). The AFSC trawl surveys and the trawls of the present study were compared using two sample t-tests (ttest2 function in MATLAB) for total biomass, fish biomass, and invertebrate biomass.

Results Spatial organization of epibenthic shelf communities Between both years, 39 trawls were conducted at 12 islands (Table 1). A total of 304 unique taxa were identified among all trawls (see Appendix). Average total trawl biomass was 1.28 ± 2.50 kg 100 m-2 (mean ± s.d.), ranging from 0.06 kg 100 m-2 for trawl 33 () to 13.95 kg 100 m-2 for trawl 24 (Amchitka). There were no significant differences in total trawl biomass among regions (F = 1.44, df = 3, P = 0.25) or islands within regions (F = 1, df = 8, P = 0.46; Figure 3). Average abundance was 68 ± 72 individuals 100 m-2, ranging from 7.0 individuals 100 m-2 for trawl 33 (Kiska) to 305.3 individuals 100 m-2 for trawl 1 (Tanaga). There were no significant differences in total abundance among regions (F = 1.31, df = 3, P = 0.29) or islands within regions (F = 1.79, df = 8, P = 0.12; Figure 4). An average of 24 ± 13 taxa was encountered per trawl, with a minimum of four taxa for trawl 28 (Attu) and a maximum of 53 taxa for trawl 16 (Unalaska). There were differences in taxon richness among regions (F = 3.87, df = 3, P = 0.02; Figure 5). From pairwise comparisons, the Far West region had significantly lower taxon

15 richness than the Central and East regions (P < 0.05; Figure 5). There were no differences in taxon richness among islands within regions (F = 1.05, df = 8, P = 0.42). Epibenthic community structure based on biomass differed among regions (Pseudo-F = 1.86, df = 3, P = 0.02, 19.2% of total estimated variance). The Far West region had the most distinct shelf community structure of all regions; the shelf community significantly differed from the Central and East regions, but was marginally non-significant from the West region (Table 2). Additionally, there were significant differences in epibenthic shelf community structure among islands within regions (PERMANOVA: Pseudo-F = 1.88, df = 8, P = 0.001, 27.1% of total estimated variance). From pairwise comparisons, Adak differed from all other islands within the Central region, but there were no differences among islands in the other regions (Table 3). Epibenthic community structure based on abundance also differed among regions (Pseudo-F = 1.73, df = 3, P = 0.03, 12.0% of estimated variance). Again, the Far West region differed from Central and East regions, but not the West region (Table 4). There also were differences in community structure among islands (Pseudo-F = 2.17, df = 8, P = 0.001, 22.4% of estimated variance). Adak differed from all islands within the Central region and Yunaska significantly differed from Tanaga, but not from any other island in the Central region besides Adak (Table 5). There were no significant differences in epibenthic shelf community structure among islands within the Far West, West, and East regions (Table 5). The ten taxa that best represented epibenthic shelf community structure across the Aleutians in terms of biomass were the bryozoan Alcyonidium spp., the flounder Atheresthes spp., crangonid shrimp, the sand dollar Echinarachnius parma, hydrozoans, the flatfish Lepidopsetta spp., the brittle star Ophiura sarsii, the hermit crab Pagurus spp., the sea urchin Strongylocentrotus spp. (primarily S. polcanthus but likely also included S. droebachiensis), and an unidentified sponge taxon (“Porifera sp. 1”) (BVSTEP Primer-e, p = 0.857; Figure 6). Of the enumerable taxa (excluding colonial organisms), the seven taxa that best represented epibenthic shelf communities in terms of abundance were the scallop Chlamys rubida, crangonid shrimp, hippolytid shrimp, the flatfish Lepidopsetta spp., the brittle stars Ophiopholis aculeata and O. sarsii, and Strongylocentrotus spp. (p = 0.855; Figure 7).

16 The three taxa that typified the Far West region in terms of biomass were (in decreasing order of importance) E. parma, crangonid shrimp, and Lepidopsetta spp. The three taxa that best distinguished the Far West from the other regions were E. parma (high density at Far West) and Strongylocentrotus spp. and O. sarsii (low density at Far West; Figure 8). The six taxa that typified Adak in terms of biomass were Atheresthes spp., crangonid shrimp, hippolytid shrimp, the hermit crab Labidochirus splendescens, the tanner crab Chionoecetes bairdi, and the snail Boreotrophon spp. The three taxa that best distinguished Adak from other islands in the Central region were Strongylocentrotus spp. and O. sarsii (low density at Adak) and C. bairdi (high density at Adak; Figure 9). The three taxa that typified the Far West in terms of abundance were crangonid shrimp, E. parma, and Lepidopsetta spp. The three taxa that best distinguished the Far West from the other regions were E. parma (high density at Far West) and O. sarsii and Strongylocentrotus spp. (low density at Far West). The six taxa that typified Adak in terms of abundance were crangonid and hippolytid shrimp, L. splendescens, C. bairdi, Boreotrophon spp., and Atheresthes spp. The three taxa that best distinguished Adak from other islands in the Central region were Strongylocentrotus spp. and O. sarsii (low density at Adak) and Boreotrophon spp. (high density at Adak).

Environmental drivers Bottom water temperature was determined for each trawl, but these point-in-time temperature measurements may not represent the long-term benthic thermal environment. Bottom water temperatures collected from the present study (Jun 2016 and July 2017) and from the longer-term AFSC bottom trawl surveys (Jun-Aug, 2010-2016) on the shelf (< 200 m depth) were plotted against Arc Distance (Figure 10). There were significant differences in bottom temperature between the two studies (F = 26.8, df = 1, P < 0.001) and among regions (F = 10.88, df = 3, P < 0.001). There was also an interaction effect between the region and survey (F = 9.89, df = 3, P < 0.001). From pairwise comparisons, bottom temperatures measured in the present study were warmer than the AFSC surveys in both the Far West and East regions. Therefore, this study's trawl bottom water temperatures are likely not representative of the long-term thermal environment across the entire study region. However, given that the

17 measurements from this study are the best available representation of the thermal environment at the specific trawl locations, they were included as a potential driver of Aleutian epibenthic shelf community structure. The combination of environmental drivers that was most highly correlated to patterns of epibenthic shelf community biomass (all sites, excluding sediment) was arc distance and exposure (p = 0.304, P = 0.01). Using just the sites where sediment was collected, the most important drivers were arc distance, bottom water temperature, and sediment grain size (p = 0.504, P = 0.01). The combination of environmental drivers that most highly correlated to patterns in abundance (all sites, excluding sediment) was arc distance and exposure (p = 0.285, P = 0.01). Using just the sites where sediment was collected, the most important drivers were arc distance, bottom water temperature, and sediment grain size (p = 0.574, P = 0.01). There was no evidence for differences among regions in terms of exposure (F = 2.43, df = 3, P = 0.0817) or sediment grain size (F = 0.71, df = 2, P = 0.5064). There were differences in bottom water temperature among regions (F = 4.716, df = 3, P < 0.001; Figure 11). The East region had significantly warmer temperatures than the other regions (P < 0.05). None of the environmental drivers identified by Bio-Env analysis besides arc distance distinguished the Far West from the other regions. There were significant differences among islands in the Central region in terms of exposure (F = 32.37, df = 4, P < 0.001; Figure 12). Adak had significantly lower exposure than any of the other islands (P < 0.05). There were also significant differences in sediment grain size among Adak, Atka, and Yunaska, which were the Central islands sampled in 2017 (F = 87.71, df = 2, P < 0.001; Figure 12). Adak had the finest grained sediment (largest φ), Atka had intermediate grain size, and Yunaska had the coarsest sediment. Finally, there were differences in bottom water temperature among islands in the Central region (F = 16.76, df = 4, P < 0.001; Figure 12). Tanaga had lower bottom water temperatures compared to Adak, Atka, and Chuginadak, but did not differ from Yunaska. Atka had warmer bottom water temperatures than Tanaga, Adak, and Yunaska, but did not differ from Chuginadak. Therefore, Adak could be distinguished from other islands in the Central region by low exposure and fine grained sediment, and Yunaska was distinguished by coarse grained sediment.

18 E. parma strongly distinguished the Far Western region from other regions. E. parma may be distributed according to bottom sediment properties (Brown, 1984; Sisson et al., 2002; Stanley and James, 1971). Sediment grain size and chlorophyll content were compared between sites that hosted E. parma versus sites without E. parma for all sites with sediment data available. There was no significant difference in either sediment property (grain size: T = 0.88, P = 0.39; chlorophyll: T = 1.28, P = 0.22). Examination of wind data at Adak revealed that the winds observed over several years were predominately from the west and west-southwest directions (Figure 13). Therefore, winds near the trawl sites at Adak primarly blew over the land rather than the ocean.

AFSC trawl survey comparisons There was no significant difference in total biomass between the AFSC Aleutian Trawl surveys and the present study (t = 1.787, df = 576, P = 0.073; Figure 14). However, the total fish biomass was significantly greater in the AFSC surveys than in the present study (t = 2.140, df = 576, P = 0.033; Figure 14). In contrast, the total invertebrate biomass was significantly lower in the AFSC surveys than in the present study (t = -9.860, df = 576, P < 0.001; Figure 14).

Discussion Aleutian epibenthic shelf communities varied among oceanographic regions and among islands in the Central region. These biological divisions occasionally matched divisions in environmental characteristics. Specifically, the Far Western region (separated from the West region by Buldir Strait) had the most distinct epibenthic shelf community structure primarily due to high densities of E. parma and low densities of Strongylocentrotus spp. and O. sarsii. However, none of the measured environmental drivers could explain the biogeographic separation of the Far West from other regions. Within the Central region, Adak had the lowest exposure and finest-grained sediment of all the islands and hosted a distinct shelf community, which was typified by Atheresthes spp. and C. bairdi and had relatively low densities of Strongylocentrotus spp. Yunaska hosted a community that was distinct from some, but not all, islands within the Central region in terms of abundance only. Yunaska had coarser grained sediment as well as high densities of Strongylocentrotus spp. while crangonid and hippolytid

19 shrimp were absent. There were no differences observed among regions or islands within regions in terms of total benthic biomass, abundance, or taxon richness. Benthic biomass in high latitude systems can be strongly influenced by the strength of pelagic-benthic coupling that characterizes food availability to the benthos. For example, Aleutian epibenthic shelf community biomass was somewhat lower compared to epibenthic communities sampled in the more northern and tightly coupled Chukchi Sea using similar survey methods [present study: 1.28 kg 100 m-2; Chukchi: 3.89 kg 100 m-2 (Bluhm et al., 2009)]. In a comparison of the trophic relationships of the Aleutian Islands, eastern Bering Sea, and Gulf of Alaska, the Aleutian Islands had the most energy passing through pelagic consumers relative to benthic consumers (Aydin et al., 2007b). In contrast, most of the biomass in the eastern Chukchi Sea was concentrated in benthic communities (Whitehouse et al., 2014). This latitudinal shift may be explained by how energy pathways differ for each system. In the eastern Bering Sea, a pelagic-dominated ecosystem on the ice-free southern Bering Sea shelf shifts to a more benthic-dominated ecosystem on the seasonally-ice covered northern shelf (Stevenson and Lauth, 2012). Also, during cool years, an intense phytoplankton bloom occurs at the ice edge in the southeastern Bering Sea with little of the production consumed by zooplankton, whereas much of the primary production is consumed by zooplankton during warm years with little ice extent (Coyle and Pinchuk, 2002). In ice-influenced regions, large seasonal pulses of primary production are, therefore, channeled in tight pelagic-benthic coupling to support infaunal and epifaunal communities (Grebmeier et al., 2006, 1988). The latitudinal shift from a pelagic-dominated system to a benthic-dominated system in the eastern Bering Sea manifests as a decrease in the relative proportion of fish to invertebrates captured in trawl surveys from south to north (Stevenson and Lauth, 2012). Sea ice does not reach the Aleutians even under maximum sea ice extent in the Bering Sea (Overland and Pease, 1982). Therefore, it is likely that the Aleutian Islands function more as a pelagic-dominated food web where much of the pelagic primary production is removed by pelagic consumers and therefore unavailable for Aleutian benthic communities. Bottom water temperatures measured in the present study exceeded previous measurements by AFSC surveys in the Eastern and Far Western regions. The warmer

20 temperatures may have been due to sampling at shallower locations in the present study compared to the AFSC surveys. Alternatively, the recent warm temperatures may have been related to a heat wave, which was first noted in Alaskan waters in 2014 (Freeland, 2014) but peaked in 2016 (Walsh et al., 2018), coinciding with the first year of sampling for the present study. The warm temperature anomaly, referred to as the “blob”, affected both the Gulf of Alaska and the Bering Sea with the warmest sea surface temperatures on record in the Bering Sea (Walsh et al., 2018). Heating from the “blob” may have affected the East region of the Aleutians more than the Central region. However, there was no evidence of a break in epibenthic community structure between the Central and East region in association with this break in temperature. Shifts in community structure may occur as water temperature changes (Schiel et al., 2004; Somero, 2005), but the benthic community response time to changing conditions depends on multiple factors, including the generation time of community members (Coyle et al., 2007). Multiple Aleutian epibenthic shelf community members are long lived; for instance, Ophiura sarsii has a maximum age of 27 years (Ravelo et al., 2017), and Strongylocentrotus droebachiensis may live longer than 50 years (Russell et al., 1998). Hence, as long as the elevated temperatures are within the general physiological tolerance windows of the adults, responses on the population level to warming termperatures will likely take multiple years to become effective. If the raised temperatures do not impact adult epibenthic community members but do affect the more sensitive larval stage (Dupont et al., 2010; Verween et al., 2007), then any shift in community structure will be offset from the timing of the heat wave event as the new larval community enters the adult population. Aleutian epibenthic shelf communities should be monitored over the next several years to determine whether a lagged response to the warming anomaly occurs. This information would be valuable for improving forecasts of the response of Aleutian communities to changing climate. Arc distance was a strong predictor of relationships among the epibenthic shelf communities. The tendancy for communities to be most similar when located in proximity to each other is consistent with the theory of distance decay of similarity for ecological communities (Nekola and White, 1999; Soininen et al., 2007). The decline of similarity with distance can be explained by the decreasing similarity in environmental features (Nekola and

21 White, 1999) or by the limited dispersal of organisms (Hubbell, 2001). In this study, arc distance was selected by the models because communities were frequently more similar when they were close to each other. However, the patterns of community similarity were not described as a steady decay in similarity across the island chain but rather an abrupt shift in community structure across Buldir Strait. It was largely due to the observed break in community structure between the Far West and the other regions that arc distance was identified as a strong predictor of community patterns. Therefore, it is likely that environmental features are dissimilar across Buldir Strait (Nekola and White, 1999) or the dispersal of organisms is hampered across the pass (Hubbell, 2001). One of the species driving the community dissimilarity of the Far West compared to other regions was E. parma but it is unclear why E. parma occurred frequently and in high densities in the Far West. Given the limited number of samples collected per island, it is possible the trawls simply missed collecting E. parma at various islands in the West, Central, and East regions due to chance. However, there were few areas of flat substrate (and thus presumably soft sediment) to select from that were within 15 km of nearshore sampling locations at most islands. Therefore, it is likely that the selected offshore sampling locations were representative of flat-bottom communities. Regardless, the drivers for the presence or absence of E. parma remains of interest. The distribution of E. parma is largely governed by associations with particular sediment characteristics (Brown, 1984; Sisson et al., 2002; Stanley and James, 1971). At intermediate grain sizes, sediment may trap enough particulate organic matter to sustain E. parma, without trapping so much that the decomposing organic matter “fouls” the sediment and deters sand dollars (Parker, 1927; Stanley and James, 1971). In this study, neither sediment grain size nor chlorophyll content could explain why sites with E. parma were distinct from sites without E. parma. Whatever the cause, if E. parma distribution is linked to some environmental variable or ecological interaction, this driving feature likely changes across Buldir Strait. Multiple investigations of Aleutian animal populations have documented a biogeographic separation of populations at the Far Western Islands from and the other islands in the Western region. This biogeographic separation may be related to changes in the extent of the continental shelf across Buldir Strait (Springer et al., 1996). The broad, shallow

22 shelf that characterizes the Near Islands (Far West) creates a coastal enviroment similar to that of the eastern Bering Sea shelf, while Buldir Island sits on a shallow, steep shelf (Springer et al., 1996). The wide shelf of the Near Islands promotes the development of an extensive coastal forage fish community while limiting the abundance of large-bodied, oceanic zooplankton (Springer et al., 1996). In turn, thick-billed murres, which prefer to forage on coastal forage fish, are abundant in the Far West, while common murres, which prefer zooplankton prey, are common at Buldir Island (Springer et al., 1996). Other studies have documented differences between the ecology of the Far Western region and the Western region, but have yet to identify the environmental drivers. Multiple sea birds have declined precipitously in the Far West since the 1970s (Byrd and Williams, 2004). Simarly, the greatest declines for harbor seals occurred within the Far West (Small et al., 2008). Additionally, the sea urchin (Strongylocentrotus spp.) population structure in the Far West has diverged from population structures elsewhere due to increases in the relative proportion of large-bodied individuals (Weitzman et al., unpub data). The present study supports the above-mentioned other research that suggested a biogeographic separation of the Far Western islands from other Aleutian islands. This could have significant implications for the ecological management of the Aleutians, especially considering that the Far Western and Western Aleutians are freqeuntly lumped into as a single Western region for management purposes (Aydin et al., 2007a; Zador, 2016). The separation of the Far Western and Western communities seen in the present study may be explained by oceanographic currents. For instance, the AS forms meanders and eddies to the west of Amchitka Pass, separating the West and Central regions, (Stabeno and Reed, 1994; Thomson, 1972). If these temporally-unstable oceanographic features are more typical within the Far West than the West and enhance cross-shelf exchange of nutrients, for example (Mizobata et al., 2006), this might contribute to the unique oceanographic environment at the Far West. Oceanographic descriptions in the Far Western Aleutians are presently limited to satellite-tracked buoys deployed in the late 1980's and early 1990's (Reed and Stabeno, 1993; Stabeno and Reed, 1994, 1992) as well as hydrographic surveys from a 1992 research cruise and moorings deployed from 1991-92 (Reed and Stabeno, 1993). Without additional information

23 on current oceanographic conditoins, it is difficult to explain the biogeographic separation of the various biological communities that have been found in the Far Western Aleutians. It is somewhat surprising that there was no evidence of a separation of epibenthic communities between the East region and other regions in the present study. There are important ecological differences for multiple communities across Samalga driven by changes in oceanography (Hunt and Stabeno, 2005). In particular, studies reference the influence of the warm and fresh ACC to the east of the pass versus the cold and saline AS to the west (Ladd et al., 2005). For example, the zooplankton community switched from neritic taxa east of Samalga Pass to oceanic taxa west of Samalga Pass, and this variability was highly correlated with changes in water temperature and salinity (Coyle, 2005). In contrast, the results of the present investigation do not suggest that epibenthic communities differ across Samalga Pass. There are numerous epibenthic shelf taxa that occurred on either side of Samalga and throughout the Aleutians, including the very common urchins and brittle stars. This suggests that shelf communities on either side of Samalga Pass to some degree share a common pool of larvae to replace the continual loss of organisms (Underwood and Fairweather, 1989). The wide dispersal range for some epibenthic taxa may contribute to the homogeneity in the Aleutian epibenthic shelf community structure across large spatial scales. For example, the urchin Strongylocentrotus droebachiensis, which occurs across the Aleutians, can remain in the pelagic larval phase for over 21 weeks (Strathmann, 1978). In addition to the length of the larval phase, dispersal also depends on water motion supporting the translocation of larvae. The northern portion of the Alaskan Stream has geostrophic flow exceeding 20 cm s-1 with the northern edge of the Stream in excess of 90 cm s-1 (Stabeno and Reed, 1991). Assuming flow of 20 cm s-1, S. droebachiensis larvae could travel the 1900 km length of the Aleutian Islands in just over 15 weeks, well within its maximum pelagic duration. In contrast, those communities that have ecological differences across Samalga Pass likely include organisms with more limited dispersal ranges. For example, the diversity of Aleutian cold-water corals declines from west of Samalga Pass to east of the pass (Heifetz, 2002). Tropical corals have relatively limited larval pelagic durations and short dispersal distances (< 4.5 days and < 1 km, respectively; Sammarco and Andrews, 1989; Sebens, 1983; Shanks, 2009; Shanks et al., 2003). The dispersal abilities of cold

24 water corals are likely similarly limited (Davies et al., 2008; Rooper et al., 2014), possibly limiting their dispersal across the strong flow of Samalga Pass. Indeed, due to the differing ecologies of various epibenthic organisms, particular community members may exhibit biogeographic variability at Samalga Pass or elsewhere while other community members do not. Adak Island had a distinct shelf community within the Central region, likely due to its softer sediment. Compared to other islands in the Central region, Adak hosted fewer sea urchins (Strongylocentrotus spp.) and more C. bairdi and Atheresthes spp. Out of all the sampled islands, Adak had the lowest exposure (13.9-19.4%) and and the finest-grained sediment (φ: 4.42-5.32). Multiple taxa that characterized the epibenthic shelf community at Adak are typical of muddy communities. The Tanner crab (C. bairdi) has been observed in dense mating aggregations on extensive muddy sediment (Stevens et al., 1994). Flatfish, including Atheresthes stomias, also prefer muddy sediment for burrowing (Moles and Norcross, 1995). In contrast, the muddy sediment at Adak may not be preferred habitat for sea urchins, which occured in relatively low density at Adak compared to other islands in the Central region. In New Zealand, juvenile urchins (Evechinus chloroticus) were more abundant on wave-exposed reefs compared to protected reefs, as fine sediment both inhibited larval settlement and reduced the survival of recruits (Walker, 2007). Finding the muddy community at Adak in this study is likely a consequence of sampling at protected locations with low energy environments (Bergen et al., 2001). This is supported both by the low exposure quantified for the sites at Adak and by an examination of the prevailing winds, which blow primarly over land rather than the ocean. As such, wind-generated turbulence is expected to be relatively minor within the embayment in which the trawls were completed. It is possible that the muddy sediment at Adak is largely constrained to Kuluk Bay (in which all the sites were located) and may not be typical for shelf habitat elsewhere on the island. Unfortunately, none of the previous AFSC trawl sites were located within Kuluk Bay; therefore, it is currently impossible to compare this embayment with other shelf habitat on Adak. Future research on Aleutian epibenthic shelf communities should prioritize sampling at multiple geographic locations on each island, including areas of differing exposure, to examine potential within-island variability.

25 There was weaker evidence for a unique shelf community at Yunaska Island in the Central region than for Adak. Yunaska differed from two other Central islands (Adak and Tanaga) by abundance only. Typifying taxa for Yunaska included sea urchins, unidentified sculpins, snailfish, and the seastar Pteraster marsippus. Within the Central region, Yunaska had the coarsest sediment, which may account for the relatively high densities of sea urchins. However, given that Yunaska only differed from the two islands in the Central region, and only in terms of abundance, these findings should be viewed cautiously. Comparisons between the estimated densities of epibenthic shelf organisms as determined by this study and the AFSC trawl surveys suggests that there are significant differences in the sampling effectiveness between the sampling gear and survey methods used in the two studies. Invertebrates appeared to be sampled ten times as effectively in this study compared to the AFSC trawl surveys, while the AFSC reported fish catches two magnitudes greater than in this study. Reasons for catch differences may be because the AFSC Poly Nor'Eastern trawl net is equipped with roller gear designed to bounce over rocks, making it well suited for long tows (15 minutes, Stauffer, 2004) over uneven substrate. The plumb staff beam trawl, which lacks roller gear, is effective in sampling demersal fish and invertebrates over soft substrate (Gunderson and Ellis, 1986). In compliance with specifications for the plumb staff beam trawl net (Gunderson and Ellis, 1986), towing speed for this project was slower (1.5 knots) than the speed for the AFSC surveys (3 knots, Stauffer, 2004). It is likely that the AFSC trawl protocols were more effective at capturing demersal fish because fish are more likely to avoid a slower moving net (Dickson, 1993) and because the 7-m vertical opening of the Poly Nor'Eastern trawl net (von Szalay et al., 2017) is greater than that of the 0.6-m plumb staff beam trawl opening (Gunderson and Ellis, 1986). Conversely, the beam trawl used in the present study is more effective at sampling epibenthic invertebrates because it maintains good bottom contact along the entire length of the footrope, while the tickler chain array dislodges organisms from the substrate, lifting them into the net (Gunderson and Ellis, 1986). By comparison, at a towing speed of 3 knots, the center bobbins of the Poly Nor'Eastern trawl net are raised off the bottom by an average of 1.8 cm (Somerton and Weinberg, 2001). In addition, the much smaller cod end mesh size of the plumb staff is more effective in retaining smaller-

26 sized benthic invertebrates. Given that the AFSC has likely been undersampling epibenthic invertebrates in their Aleutian trawl surveys, previous determinations of the abundance and distribution of these invertebrates should be viewed with caution. However, the protocols for the AFSC surveys are well suited for sampling groundfish taxa (Goddard et al., 2014), which are central to the mission of the AFSC. Surveys of epibenthic communities on the Galican continental shelf have addressed this issue by utilizing multiple net types; otter trawls were used to sample swimming and large-sized epibenthic taxa while beam trawls were used to target flat and slow fish as well as sessile and small invertebrates (Serrano et al., 2008, 2006). Future surveys of Aleutian epibenthic shelf communities should consider employing a combination of survey gear, which may target various taxonomic groups better than a single gear type.

Summary This study makes an important contribution to the understanding of the organization of Aleutian epibenthic shelf communities. A break in epibenthic community structure was observed at Buldir Strait, mostly driven by the sand dollar E. parma. The biogeographic relationships that occur within the Far Western Aleutians (west of Buldir Strait) are poorly resolved, but this study adds to the body of literature documenting significant ecological differences for various communities across Buldir Strait (Byrd and Williams, 2004; Small et al., 2008; Springer et al., 1996). Furthermore, the soft sediment community observed at Adak Island was likely constrained to Kuluk Bay, raising the possibility that there exists important variability in shelf community structure within Adak Island and possibly other islands. Samalga Pass did not appear to represent an important break in community structure, although this pass is a well known biogeographic break for multiple other biological communities (Hunt and Stabeno, 2005; Konar et al., 2017). Finally, this study demonstrated how the AFSC Aleutian trawl surveys may underrepresent some epibenthic taxa. Future research efforts to characterize Aleutian epibenthic shelf communities should take care to effectively sample as many community members as possible, thereby providing the most accurate description of these ecologically important communities.

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42 Figures and Tables

Figure 1. Map of the Aleutian Islands displaying major ocean currents (top panel), depths of oceanographic passes (middle panel), and island locations (bottom panel). Passes of interest mentioned in text are indicated by arrows. ACC: Alaska Coastal Current. ANSC: Aleutian North Slope Current. BSC: Bering Slope Current. Figure modified from Hunt and Stabeno, 2005.

43 Figure 2. Map of the Aleutian Islands indicating the islands sampled. A priori oceanographic regions (Far West, West, Central, East) are delineated by major oceanographic passes (black bars). Island symbols indicate the sampling year. The Semichi Island group is a cluster of small islands including Alaid, Nizki, and Shemya, and are treated in this study as a single island (Semichis).

44 Table 3. List of trawl site information, including the sampling year, the island and region in which the trawl was conducted, the GPS coordinates of the trawl midpoint location (decimal degrees), the arc distance (kilometers), the average trawl depth (meters) and the midpoint distance to shore (meters). Rows with grey shading indicate trawls that were damaged by rocks and were adjusted for their estimated CPUE (see text for details). Arc Dist to Trawl Year Island Region Longitude Latitude Distance Depth shore 1 2016 Tanaga Central 182.30295 51.79920 655.02 159 1735 2 2016 Tanaga Central 182.32645 51.80205 656.68 177 1391 3 2016 Tanaga Central 182.34480 51.80455 657.98 154 1433 4 2016 Adak Central 183.39765 51.86120 731.15 80 702 5 2016 Adak Central 183.40680 51.87350 732.01 74 1649 6 2016 Adak Central 183.39910 51.88190 731.64 64 1786 7 2016 Atka Central 185.35095 52.14925 869.70 70 3364 8 2016 Atka Central 185.27355 52.15020 864.52 87 3318 9 2016 Atka Central 185.38595 52.19405 873.15 86 3976 10 2016 Chuginadak Central 190.09465 52.86800 1203.10 64 1612 11 2016 Chuginadak Central 190.15155 52.90025 1207.80 85 2112 12 2016 Chuginadak Central 190.18055 52.88835 1209.30 51 1031 13 2016 East 191.07215 52.95335 1268.60 49 1998 14 2016 Umnak East 191.01320 52.96325 1265.20 59 3496 15 2016 Umnak East 191.06685 53.01325 1270.40 65 1803 16 2016 Unalaska East 192.33220 53.40120 1365.00 83 1594 17 2016 Unalaska East 192.38130 53.41000 1368.40 65 1927 18 2016 Unalaska East 192.37600 53.39680 1367.50 47 1221 19 2017 Adak Central 183.39529 51.86018 730.97 83 624 20 2017 Adak Central 183.40715 51.87393 732.04 74 1692 21 2017 Adak Central 183.40131 51.88248 731.80 68 1932 22 2017 Amchitka West 179.25526 51.44350 444.27 71 2604 23 2017 Amchitka West 179.27282 51.42712 445.58 61 1538 24 2017 Amchitka West 179.33538 51.42993 449.75 88 2678 25 2017 Semichis Far West 174.13135 52.74724 66.10 43 1669 26 2017 Semichis Far West 173.99060 52.75933 56.85 47 1431

45 27 2017 Semichis Far West 173.89783 52.79708 49.30 90 2899 28 2017 Attu Far West 173.20989 52.94847 0.00 52 1168 29 2017 Attu Far West 173.25375 52.96336 1.83 85 2268 30 2017 Attu Far West 173.27887 52.95760 3.64 79 2566 31 2017 Far West 173.50608 52.35729 47.21 69 2933 32 2017 Kiska West 177.62051 51.97332 324.46 44 939 33 2017 Kiska West 177.61013 51.99227 323.29 56 2106 34 2017 Kiska West 177.65048 51.99917 325.90 85 3131 35 2017 Atka Central 185.35233 52.14562 869.70 62 3160 36 2017 Atka Central 185.38302 52.19350 872.94 86 4120 37 2017 Yunaska Central 189.25429 52.69263 1143.10 85 1755 38 2017 Yunaska Central 189.22536 52.68181 1140.90 90 2432 39 2017 Yunaska Central 189.29228 52.70796 1146.00 83 2507

46 Figure 3. Bar plot of average island total epibenthic shelf biomass. Error bars are standard deviations. There were no differences in total biomass among regions (F = 1.44, df = 3, P = 0.2527) or islands within regions (F = 1, df = 8, P = 0.4598).

47 Figure 4. Bar plot of average island total epibenthic shelf abundance. Error bars are standard deviations. There were no differences in total biomass among regions (F = 1.31, df = 3, P = 0.2925) or islands within regions (F = 1.79, df = 8, P = 0.1226).

48 Figure 5. Bar plot of average island epibenthic shelf taxon richness. Error bars are standard deviations. Lower case letters indicate significant differences in species richness among regions. There were differences in species richness among regions (F = 3.87, df = 3, P = 0.02). From pairwise comparisons, the Far West had significantly lower species richness than the Central and East regions (P < 0.05). There were no differences in species richness among islands within regions (F = 1.05, df = 8, P = 0.4239).

49 Table 4. PERMANOVA pairwise comparisons of shelf community structure among regions by biomass. Columns represent the t-statistic for each comparison, the Monte-Carlo p-value, and the number of unique permutations possible. Region pairs with significant differences in shelf community structure are in bold.

Region pairwise comparisons by biomass

Groups t P(MC) perms Central, East 1.29 0.08 379 Central, West 0.88 0.66 378 Central, Far West 1.64 0.01 874 East, West 1.24 0.20 3 East, Far West 2.29 0.006 30 West, Far West 1.59 0.065 30

50 Table 5. PERMANOVA pairwise comparisons of shelf community structure among islands within each region by biomass. Columns represent the t-statistic for each comparison, the Monte­ Carlo p-value, and the number of unique permutations possible. Island pairs with significant differences in shelf community structure are in bold.

Unique Groups t P(MC) perms Semichis, Attu 1.02 0.40 10 Semichis, Agattu 1.01 0.46 4 Attu, Agattu 0.77 0.62 4

Unique Groups t P(MC) perms Amchitka, Kiska 1.36 0.16 10

Within level 'Central' of factor 'Region' Unique Groups t P(MC) perms Tanaga, Adak 1.86 0.02 84 Tanaga, Atka 1.21 0.21 56 Tanaga, Chuginadak 1.19 0.28 10 Tanaga, Yunaska 1.60 0.08 10 Adak, Atka 1.80 0.009 402 Adak, Chuginadak 1.98 0.006 84 Adak, Yunaska 2.24 0.006 84 Atka, Chuginadak 1.45 0.09 56 Atka, Yunaska 1.55 0.07 56 Chuginadak, Yunaska 1.27 0.18 10

Unique Groups t P(MC) perms Umnak, Unalaska 0.86 0.59 10

51 Table 6. PERMANOVA pairwise comparisons of shelf community structure among regions by abundance. Columns represent the t-statistic for each comparison, the Monte-Carlo p-value, and the number of unique permutations possible. Region pairs with significant differences in shelf community structure are in bold.

Region pairwise comparisons by abundance Unique Groups t P(MC) perms Central, East 1.15 0.24 384 Central, West 0.89 0.62 381 Central, Far West 1.60 0.01 855 East, West 1.37 0.14 3 East, Far West 2.28 0.008 30 West, Far West 1.58 0.07 30

52 Table 7. PERMANOVA pairwise comparisons of shelf community structure among islands within each region by abundance. Columns represent the t-statistic for each comparison, the Monte­ Carlo p-value, and the number of unique permutations possible. Island pairs with significant differences in shelf community structure are in bold.

Unique Groups t P(MC) perms Semichis, Attu 1.13 0.32 10 Semichis, Agattu 0.98 0.48 4 Attu, Agattu 0.81 0.57 4

Within level 'West' of factor 'Region' Unique Groups t P(MC) perms Amchitka, Kiska 1.37 0.17 10

Within level 'Central' of factor 'Region' Unique Groups t P(MC) perms Tanaga, Adak 1.92 0.01 84 Tanaga, Atka 1.12 0.28 56 Tanaga, Chuginadak 1.32 0.19 10 Tanaga, Yunaska 1.78 0.046 10 Adak, Atka 2.07 0.003 413 Adak, Chuginadak 2.21 0.006 84 Adak, Yunaska 2.59 0.001 84 Atka, Chuginadak 1.51 0.07 56 Atka, Yunaska 1.72 0.04 56 Chuginadak, Yunaska 1.49 0.11 10

Within level 'East' of factor 'Region' Unique Groups t P(MC) perms Umnak, Unalaska 0.80 0.63 10

53 Figure 6. Map of trawl locations displaying the relative biomass of the ten taxa that best represented epibenthic community structure in terms of biomass (BVSTEP Primer-e, p = 0.857), separated by region. Numbers in the center of each pie chart indicate the trawl number (see Table 1).

54 Figure 7. Map of trawl locations displaying the relative abundance of the seven taxa that best represented epibenthic community structure in terms of abundance (BVSTEP Primer-e, p = 0.855), separated by region. Numbers in the center of each pie chart indicate the trawl number (see Table 1).

55 Figure 8. Average island biomass CPUE for the three epibenthic shelf taxa that best distinguish the Far West from the other regions.

56 Figure 9. Average island biomass CPUE for the three epibenthic shelf taxa that best distinguish Adak Island from other islands in the Central region.

57 Figure 10. Plot of trawl bottom temperatures from the present study and the AFSC trawl surveys (2010-2016) versus Arc Distance. Asterisks above region names denote significant differences in bottom temperatures measured in the present study and the AFSC trawl surveys for the indicated region. Bottom temperatures in the present study were warmer than temperatures measured in the AFSC trawl surveys for both the East and Far West regions.

58 Figure 11. Box plot of bottom temperatures for each region. Lower case letters indicate significant differences among regions in bottom temperature (P < 0.05). Upper case letters indicate significant differences among regions in epibenthic community structure by biomass.

59 Figure 12. Box plots of site-level exposure, sediment grain size (Φ), and bottom water temperature for the islands in the Central region. Lower case letters indicate significant differences among islands in exposure, grain size, or temperature (P < 0.05). Upper case letters indicate significant differences among islands in epibenthic community structure by biomass. Figure 12. Map of trawl locations at Adak Island (diamonds; n = 6 total from both years) and Station ADKA2 (Adak Island) of the NOAA National Data Buoy Center (square). Inset is a wind rose displaying the frequency of wind directions at Station ADKA2 over several years (2006-08 and 2010-17).

62 Trawl Metrics

Figure 13. Comparison of average total CPUE, fish CPUE, and invertebrate CPUE for trawls from the AFSC trawl surveys (2014 and 2016) for sites on the continental shelf (< 200 m, n = 262) and the present study (n = 39). Error bars are standard deviation. Significant differences are denoted with asterisks.

63