Bull Mar Sci. 93(2):319–338. 2017 research paper https://doi.org/10.5343/bms.2016.1038
Habitat partitioning and diurnal-nocturnal transition in the elasmobranch community of a North Carolina estuary
1, 2 * 1 Institute for Coastal Science Charles W Bangley and Policy, East Carolina Roger A Rulifson 1 University, East 5th St., Greenville, North Carolina 27858. 2 Present address: Smithsonian Environmental Research ABSTRACT.—In marine communities, resource Center, 647 Contees Wharf Rd, partitioning can be as important as abiotic environmental Edgewater, Maryland 21037. preferences in determining habitat use patterns. * Corresponding author email: Elasmobranchs are generally assumed to be crepuscular or
Marine predators can significantly influence the distributions of other species and local community dynamics (Heithaus et al. 2012). Elasmobranchs typically oc- cupy high trophic levels within marine communities, and some species function as apex predators in these ecosystems (Cortés 1999, Heithaus et al. 2010, Hussey et al. 2015, Shaw et al. 2016). Even at relatively small spatial and temporal scales, elasmobranchs can have significant, population-level, top-down effects on prey spe- cies (Beamish et al. 1992, Lacroix and Fleming 2014). The habitat use patterns of
Bulletin of Marine Science 319 © 2017 Rosenstiel School of Marine & Atmospheric Science of the University of Miami 320 Bulletin of Marine Science. Vol 93, No 2. 2017 elasmobranchs, particularly apex predator shark species, can have direct predato- ry and indirect behavioral effects throughout the food web to the level of primary producers (Burkholder et al. 2013, Vaudo and Heithaus 2013, Heithaus et al. 2014). However, elasmobranchs may not necessarily function as keystone apex predators in ecosystems with other large, mobile predators (Kitchell et al. 2002, Frisch et al. 2016), though some species may still occupy the highest trophic levels even when co- occurring with other predators (Shaw et al. 2016). Juvenile and small-bodied sharks can be among the most abundant predatory species within estuaries (Grabowski et al. 2005). Given the importance of top-down interspecific interactions in structuring estuarine ecosystems (Heck and Valentine 2007), habitat use by elasmobranchs in estuaries is deserving of detailed study. Habitat use by sharks is likely driven by a combination of abiotic factors in the form of environmental preferences, and biotic factors in the form of interspecific relationships with prey, competitors, or predators (Heithaus 2007). Depending on body size, sharks can function as apex predators or mesopredators, though local en- vironmental conditions may determine the trophic role of a given species in a given habitat (Heupel et al. 2014). In nearshore and estuarine environments, multiple shark species may coexist (Simpfendorfer and Milward 1993) and competition may lead to resource partitioning among sympatric elasmobranchs and other high tropic-level predators (Heithaus and Vaudo 2012). Resource partitioning is widespread among fishes and can be expressed as trophic, spatial, or temporal differences in habitat use between species occupying the same system (Ross 1986). Different types of re- source partitioning have been observed among elasmobranchs: species with similar prey preferences showed differences in spatial habitat use within Apalachicola Bay (Bethea et al. 2004), while different species occupying the same spatial area within Cleveland Bay showed evidence of trophic resource partitioning (Kinney et al. 2011). Temporal separation was the primary form of resource partitioning between fishes in 11% of studies assessed by Ross (1986) and may be important in structuring elas- mobranch communities, but diel temporal influences on habitat use and resource partitioning are not well-known in elasmobranchs (Hammerschlag et al. 2017). A variety of methods can be used to investigate habitat use by elasmobranchs, and each approach has its own unique set of requirements and limitations (Simpfendorfer and Heupel 2012). While catch rates from fishery-independent surveys can cover a broad spatial area, diel differences in habitat use patterns have been assessed most- ly using various forms of telemetry to cover the entire 24-hr cycle (Simpfendorfer and Heupel 2012, Donaldson et al. 2014). Few standardized fishery-independent surveys have assessed diel habitat use by elasmobranchs; in one such study, four of six Carcharhinid shark species captured in longline surveys along the southeastern coast of the United States were caught primarily at night (Driggers et al. 2012). To help fill this knowledge gap, we incorporated set time, with a focus on the transition from diurnal to nocturnal periods, among the variables recorded during fishery-in- dependent sampling to account for potential temporal effects on habitat preferences and resource partitioning among the elasmobranch community of a relatively small, warm-temperate estuary. Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 321
Figure 1. Fishery-independent gillnet, longline, rod-and-reel, and drumline sampling locations, known seagrass extent, and sampling strata boundaries from 2014 to 2015 elasmobranch surveys within Back and Core Sounds, North Carolina. Bold numbers identify sampling strata.
Methods
Elasmobranchs were captured during a shark survey conducted in Back and Core Sounds, North Carolina, using gillnet, longline, drumline, and rod-and-reel gear (Fig. 1). Each gear was intended to target different species groups or size classes. Gillnet gear was used to capture small-bodied species (300–1000 mm TL) and species unlikely to feed on longline bait. Longline gear targeted mid-sized species (700–1800 mm TL), and drumline gear was used to account for large, apex predatory species (>1800 mm TL). Gillnet gear measured 45 m in length and 2 m in height, and was comprised of five 9-m panels ranging from 2.5- to 14-cm stretched mesh. Longline gear consisted of a 274-m mainline with 20–30 gangions constructed of 1 m of 136 kg-test monofilament line and a 12/0 circle hook. Drumline gear consisted of a single 15-m long, 408.23 kg-test monofilament leader with a 15/0 circle hook mounted on a 18.14-kg weight. Rod-and-reel gear was used to supplement shark catches during gillnet and longline soak times and in conditions unsafe for deployment of the other gear types, and was comprised of a single fishing rod with 18.14-kg test braided line and a 0.5-m wire leader with a 12/0 circle hook. Longline and rod-and-reel hooks were baited with cut Atlantic mackerel (Scomber scombrus Linnaeus, 1758) or Atlantic menhaden [Brevoortia tyrannus (Latrobe, 1802)], supplemented by locally available baitfish, and the drumline was baited with cut sections of spiny dogfish (Squalus acanthias Linnaeus, 1758), Atlantic sharpnose shark [Rhizoprionodon terraenovae (Richardson, 1836)], or striped bass [Morone saxatilis (Walbaum, 1792)]. We assumed that bait type would not significantly influence species composition among elasmobranchs caught using longline and drumline gear. When possible, 322 Bulletin of Marine Science. Vol 93, No 2. 2017 a combination of multiple gear types was deployed simultaneously within 100 m of each other. Soak time was limited to 30 min for all gears, though longline and drumline soak times up to 45 min occasionally occurred when these gears were simultaneously deployed with gillnet sets. Sampling occurred from March 21 to November 16, 2014, and from April 13 to October 15, 2015. Sampling was not attempted during winter months due to the expected low abundance of sharks within the estuary at that time (Grabowski et al. 2005). In an attempt to focus on the crepuscular period when elasmobranchs are thought to be most active, most sampling occurred between 12:00 and 22:00, though some sets were deployed opportunistically during other hours. Sampling sites were chosen using a stratified-random strategy in which the area from lower Newport River to Jarrett Bay was divided into five major strata based on environmental dif- ferences observed during previous pilot studies (Fig. 1). Stratum 1 covered the low- er Newport River and Stratum 2 covered western Back Sound and Beaufort Inlet. Stratum 3 included the North River and Middle Marsh, an isolated salt marsh in central Back Sound. Stratum 4 covered eastern Back Sound and Harkers Island, and Stratum 5 covered Core Sound north into to Jarrett Bay and south to Barden’s Inlet. Each stratum was further divided into 6–9 numbered substrata of approximately equal area. Three substrata were randomly chosen before each sampling date with the goal of deploying three sets within each stratum every month. Exact sampling locations within substrata were chosen haphazardly based on local conditions and boat traffic (Fig. 1). At each station, depth (m) was recorded using an onboard depth sounder, and temperature (°C), salinity, and dissolved oxygen (mg L−1) were recorded from the middle of the water column using a YSI Pro 2030. Set time (hh:mm) was recorded at time of gear deployment. All sampling locations were plotted in ArcGIS 10.1, and straight-line distance from the nearest inlet (km) and the nearest seagrass bed (m) were calculated using the spatial join function. Inlet locations were represented by lines manually drawn across the entrances to Beaufort and Barden’s Inlets in ArcGIS, while seagrass bed locations were taken from layers generated by the Albemarle- Pamlico National Estuarine Partnership’s submerged aquatic vegetation (SAV) map- ping data (Kenworthy et al. 2012). Here, we refer to all of these temporal, spatial, and environmental factors collectively as habitat variables. All captured elasmobranchs were identified to species and sexed, and were record- ed. Total length (TL, mm) and fork length (FL, mm) were recorded for all sharks, and maximum disc width (DW, mm) was recorded for all batoids. For each species, mean habitat variables were calculated. Species with catches >10 individuals in the survey were considered principal species for further analysis, with the exception of the blacktip shark [Carcharhinus limbatus (Müller and Henle, 1839)], which was a target species in the survey and included in further analysis despite a lower sample size. Elasmobranch catch per unit effort (CPUE) was defined as the number captured per half-hour set. Catchability was assumed to be equal across gear types, though this was assessed by comparing overall CPUE using one-way analysis of variance (ANOVA) between gillnet and longline sets. The potential effect of the number of hooks in longline sets was assessed using bivariate linear regression and ANOVA procedures. Spatial overlap between principal species was expressed as the percentage of sets in which a given species was captured and which also contained the other species. For Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 323 the purpose of this analysis, species captured using simultaneously deployed gear types were considered to spatially overlap. Discriminant function analysis (DFA) was used to determine the extent to which the principal species could be correctly clas- sified based on habitat variables alone. Temporal habitat use was assessed using two methods: comparisons between diel time periods and circular statistics. Comparisons between diel time periods were assessed by grouping set times into day (07:30–18:00), night (20:00–05:00), and twilight (05:00–07:30 or 18:00-20:00). One-way ANOVA and Tukey’s honestly sig- nificant difference (HSD) procedures were used to determine whether differences in CPUE between diel time periods were significant. For circular statistics, set time was checked for a VonMises distribution using Watson’s U2 test and for a bias in time distribution using Rayleigh’s test of uniformity (Fisher 1993, Zar 1999) prior to comparisons between species. Watson’s two-sample test was used for comparisons between mean set time for each species and overall set time, and for pairwise com- parisons between species. All variables other than set time were checked for a normal distribution using histogram and qq (i.e., quantile-quantile) plot analysis. Habitat differences between species were tested for significance using one-way ANOVA procedure. Tukey’s HSD analysis was used to make pairwise comparisons in habitat variables between species. Statistics involving set time were calculated using the package circular in R to ac- count for the circular nature of time data, while calculations involving all other vari- ables were performed in JMP Pro 12. For all analyses, the threshold for significance was P < 0.10.
Results
Sampling covered a time frame between 07:00 and 02:00 the following day, though most survey sets occurred between 11:00 and 21:00 (Fig. 2). Mean set time was 16:07 (SD 0:55). Watson’s test of uniformity showed that set time data fit a VonMises distri- bution (U2 = 0.1633, P < 0.01) and Rayleigh’s test of uniformity showed that the time covered by the survey fit a definite temporal range (Z = 0.656, P < 0.01). All other factors fit a normal distribution. CPUE did not differ significantly between gillnet [mean CPUE = 0.70 (SD 1.13) sharks per set] and longline [mean CPUE = 1.13 (SD 2.38) sharks per set] sets (F = 2.38, P = 0.124, df = 1). The effect of number of hooks on total elasmobranch catch was significant F( = 2.88, P = 0.093, df = 1). When two sets with catches of 12 and 15 spiny dogfish were removed, the effect of hook number was not significant F( = 2.27, P = 0.135, df =1). Over both sampling years, 160 elasmobranchs of 12 positively identified species were captured (Table 1). In addition, two sharks visually identified as members of the genus Carcharhinus broke out of the gear before they could be brought onboard and processed. The most common elasmobranchs captured were spiny dogfish, Atlantic sharpnose shark, and southern stingray (Dasyatis americana Hildebrand and Schroeder, 1928). Length measurements for the Atlantic sharpnose shark cov- ered neonate to mature adult size ranges (Loefer and Sedberry 2003). All blacktip sharks fell within age 1+ juvenile size ranges, and juveniles also were present among bluntnose stingrays [Dasyatis say (Lesueur, 1817)], cownose rays [Rhinoptera bo- nasus (Mitchill, 1815)], sandbar sharks [Carcharhinus plumbeus (Nardo, 1827)], smooth dogfish Mustelus[ canis (Mitchill, 1815)], and southern stingrays (Smith and 324 Bulletin of Marine Science. Vol 93, No 2. 2017
Figure 2. Rose diagram showing the temporal distribution of sampling effort within Back and Core Sounds over a 24-hr diel cycle. Merriner 1987, Sminkey and Musick 1995, Conrath and Musick 2002, Barry et al. 2008, Henningsen and Leaf 2010). Only subadult or adult size classes of blacknose sharks [Carcharhinus acronotus (Poey, 1860)], bull sharks [Carcharhinus leucas (Müller and Henle, 1839)], bonnetheads [Sphyrna tiburo (Linneaus, 1758)], and spiny dogfish were captured (Schwartz 1984, Castro 1993, Bubley et al. 2012, Natanson et al. 2014) (Table 1). Mean time of capture for the majority of species was in mid-af- ternoon (15:30–17:30), though blacknose, bull, and sandbar sharks were caught dur- ing late twilight/night hours, and bonnetheads were captured during morning hours (07:30–11:00; Table 2). Spiny and smooth dogfish were captured at the lowest mean temperatures of any species. Bonnetheads, Carcharhinus sp., and cownose rays were caught at the lowest salinities, while all species were captured in relatively normoxic
Table 1. Total catch, catch by gear (DL = drumline, GN = gillnet, LL = longline, RR = rod and reel), and minimum and maximum total length and fork length/disc width (mm) for species captured during 2014–2015 elasmobranch sampling in Back and Core Sounds, North Carolina. Species marked with an asterisk were considered principal species for further analysis.
Catch by gear Species Total catch DL GN LL RR Min–max TL/DW (mm) Atlantic sharpnose shark* 33 0 6 26 1 326–1,000 Blacknose shark* 13 1 0 12 0 990–1,320 Blacktip shark* 7 0 0 7 0 1,112–1,295 Bluntnose stingray 5 0 5 0 0 150–450 Bonnethead 3 0 3 0 0 955–1,080 Bull shark 1 1 0 0 0 2,500 Bullnose ray 4 0 4 0 0 436–458 Carcharhinus sp. 2 0 2 0 0 – Cownose ray* 12 0 9 3 0 414–1,016 Sandbar shark 3 0 0 3 0 1,219–1,600 Smooth dogfish* 10 0 4 6 0 605–1,265 Southern stingray* 27 0 3 24 0 405–960 Spiny dogfish* 40 0 5 32 3 790–970 Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 325 40.5 (10.3) 33.9 (38.1) 219.3 (200.3) 665.8 (525.5) 489.4 (385.9) 389.9 (494.2) 246.0 (143.2) 490.3 179.8 (145.6) 228.8 559.2 (637.7) 791.5 (639.2) 569.7 (420.4) SAV distance (m) SAV 5.6 (2.7) 4.8 (2.8) 7.7 (5.4) 5.3 (4.3) 7.9 (5.2) 1.2 6.3 (2.0) 5.4 (1.6) 9.5 (5.3) 3.5 (2.2) 6.7 (5.0) 11.0 (5.3) 11.0 15.5 Inlet distance (km) ) −1 8.2 (0.4) 9.8 (2.6) 8.2 (0.7) 8.4 (1.4) 7.6 (0.7) 8.8 (1.4) 8.4 7.3 6.8 (0.2) 7.9 (0.7) 6.7 (1.5) 8.4 (1.4) 8.0 (1.5) DO (mg L Salinity 35.4 (1.0) 32.2 (4.7) 34.2 (2.4) 34.5 (2.7) 33.4 (0.5) 30.0 (2.4) 38.6 28.5 27.9 (1.0) 32.7 (1.0) 31.6 (3.5) 34.5 (2.9) 32.3 (3.4) 20.1 (1.6) 28.0 (1.3) 21.5 (3.8) 24.3 (4.7) 24.1 (1.0) 25.5 (3.4) 29.0 22.8 25.9 (1.6) 26.3 (3.8) 29.3 (0.9) 26.0 (2.8) 26.6 (3.1) Temp (°C) Temp 2.9 (0.7) 3.2 (1.5) 2.7 (0.7) 3.4 (1.2) 2.2 (0.4) 2.1 (0.5) 3.8 2.4 1.1 (0.6) 1.4 (0.8) 2.8 (1.9) 3.2 (1.8) 2.5 (1.2) Depth (m) 11:05 17:23 (0:28) 17:06 (0:52) 17:38 (0:41) 19:44 (0:33) 13:10 (0:29) 15:32 (0:44) 19:36 10:29 (0:17) 15:51 (0:36) 15:54 (0:59) 19:08 (0:42) 16:32 (0:59) Set time (hh:mm) Spiny dogfish Southern stingray Smooth dogfish Sandbar shark Bullnose ray sp. Carcharhinus Cownose ray Bull shark Bonnethead Bluntnose stingray Blacktip shark Blacknose shark Atlantic sharpnose shark Table 2. Mean and standard deviation (SD, in parentheses) of temporal, environmental, and spatial factors for each elasmobranch species captured during 2014– species captured factors for each elasmobranch and spatial environmental, (SD, in parentheses) of temporal, 2. Mean and standard deviation Table aquatic vegetation. = submerged 2015 sampling in Back and Core Sounds, North Carolina. SAV Species 326 Bulletin of Marine Science. Vol 93, No 2. 2017 conditions. Bull and blacknose sharks were caught closest to inlets, and bullnose rays and bonnetheads were captured at the shortest distances from seagrass beds (Table 2). We selected seven most commonly-captured species as the principal species for further analysis: Atlantic sharpnose shark, blacknose shark, blacktip shark, cownose ray, smooth dogfish, southern stingray, and spiny dogfish. All principal species were caught within multiple sampling strata (Fig. 3). Atlantic sharpnose sharks and southern stingrays were the most ubiquitous species, caught in all sampling strata. However, the highest catches of southern stingrays were clus- tered in the southwest area of stratum 3, near Middle Marsh. Most catches of blac- knose sharks were also captured within this area, while nearly all blacktip sharks were captured in the eastern portions of Back Sound and north into Core Sound. The majority of captured cownose rays occurred in relatively sheltered areas. Smooth and spiny dogfish were captured in the greatest numbers in the vicinity of Middle Marsh (Fig. 3). Spatial overlap between the principal species was generally relatively low, though overlaps between blacktip sharks and southern stingrays and between smooth dog- fish and Atlantic sharpnose sharks approached 50% (Fig. 4). Atlantic sharpnose sharks showed the highest degree of spatial overlap, co-occurring (i.e., captured at same location) with all species except cownose rays. Southern stingrays also were relatively ubiquitous, co-occurring with all species except spiny dogfish and cownose rays, while smooth and spiny dogfish co-occurred with three species each. Blacknose and blacktip sharks only co-occurred with Atlantic sharpnose sharks and south- ern stingrays. Of the seven principal species, only spiny dogfish co-occurred with cownose rays (Fig. 4). Discriminant function analysis correctly classified 59.15% of sharks to species based on habitat variables alone (Wilks’ Lambda = 0.135, P < 0.0001). Canonicals 1 and 2 explained 91.9% of the variance and were driven primarily by temperature and dissolved oxygen, respectively (Table 3). Spiny and smooth dogfish appeared to be isolated from the other species by temperature, while Atlantic sharpnose and blac- knose sharks overlapped completely (Fig. 5). Spiny dogfish had the highest percent- age of correct classification (95.00%), followed by blacktip sharks (71.43%) (Table 4). Approximately half of blacknose sharks (53.85%) and smooth dogfish (50.00%) were correctly classified, and fewer than half of the individuals of all other species were correctly classified based strictly on habitat variables (Table 4). A significant difference in CPUE between diel time periods was found for the blac- knose shark, for which CPUE was highest at night (F = 4.83, P = 0.01, df = 2) (Table 5). CPUE did not differ significantly by diel time period for any other species (Table 5). Watson’s two-sample test results showed that differences between species mean set time and overall set time were significant for spiny dogfish and smooth dogfish 2 2 (Table 6). In addition, U values were not significant for blacknose sharks (U test = 2 2 2 0.12, U crit = 0.15) and cownose rays (U test = 0.12, U crit = 0.15). Mean set time for spiny dogfish differed significantly from all other principal species (Table 7). A significant difference in set time was also found between cownose rays and smooth dogfish, and a significant difference between blacknose sharks and smooth dogfish (Table 7). Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 327
Figure 3. Capture locations and total catch at 2014–2015 fishery-independent elasmobranch sur- vey stations in Back and Core Sounds: (A) Atlantic sharpnose shark (Rhizoprionodon terraeno- vae), (B) blacknose shark (Carcharhinus acronotus), (C) blacktip shark (Carcharhinus limbatus), (D) cownose ray (Rhinoptera bonasus), (E) smooth dogfish Mustelus( canis), (F) southern sting- ray (Dasyatis americana), (G) spiny dogfish Squalus( acanthias). 328 Bulletin of Marine Science. Vol 93, No 2. 2017
Figure 4. Radiographs depicting spatial overlap between each principal elasmobranch species and the other principal species, expressed as the percent of sets in which the given species was caught with the other. Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 329
Table 3. Canonical values, cumulative percent of variance explained, and correlations with environmental factors for canonicals generated by discriminant function analysis. Temp = temperature, DO = dissolved oxygen, SAV = submerged aquatic vegetation, dist = distance.
Canonical structure Canonical Eigenvalue Cumulative (%) Set time Temp Sal DO SAV dist Inlet dist 1 3.29 84.45 −0.18 0.92 −0.44 0.12 0.43 0.01 2 0.29 91.95 −0.11 0.01 −0.17 0.89 −0.09 −0.32 3 0.24 98.09 0.43 −0.08 0.68 0.23 0.47 −0.70 4 0.04 99.14 0.40 −0.23 0.09 0.27 0.59 0.17 5 0.03 99.80 0.78 0.10 −0.27 −0.05 −0.16 −0.28 6 0.01 100.00 0.04 0.29 0.48 0.27 −0.46 0.54
Significant differences between principal species were found for all non-temporal factors except depth (Table 8). Generally, smooth and spiny dogfish were grouped together by most environmental factors while Atlantic sharpnose, blacktip sharks, blacknose sharks, and southern stingrays were grouped together by temperature, sa- linity, and dissolved oxygen. The only species not grouped together by inlet distance were blacknose and blacktip sharks (Table 8).
Figure 5. Discriminant function analysis plot classifying principal elasmobranch species based on temporal, environmental, and spatial factors. Ellipses represent 95% confidence intervals. Biplot rays are placed off-center to improve legibility. 330 Bulletin of Marine Science. Vol 93, No 2. 2017
Table 4. Percentage (%) of individual sharks classified as each species based on temporal, environmental, and spatial factors using discriminant function analysis. Correct classifications are in bold.Atl = Atlantic.
Atl sharpnose Blacknose Blacktip Cownose Smooth Southern Spiny Species shark shark shark ray dogfish stingray dogfish Atl sharpnose shark 33.3 21.2 9.1 0.0 6.1 27.3 3.0 Blacknose shark 0.0 53.8 0.0 0.0 15.4 30.8 0.0 Blacktip shark 0.0 14.3 71.4 14.3 0.0 0.0 0.0 Cownose ray 8.3 0.0 0.0 41.7 16.7 25.0 8.3 Smooth dogfish 20.0 0.0 0.0 10.0 50.0 0.0 20.0 Southern stingray 14.8 7.4 11.1 18.5 0.0 48.1 0.0 Spiny dogfish 0.0 0.0 0.0 0.0 5.0 0.0 95.0
Discussion
Catch data from a fishery-independent survey revealed that most of the principal elasmobranch species examined in our study from Back and Core Sounds are habitat generalists. Evidence of spatial resource partitioning was found between two of the seven principal elasmobranch species, with some potential evidence for temporal re- source partitioning on a diel and seasonal scale. Though it is clear that more data are needed, the results from our study provide basic data on elasmobranch habitat use in this estuary that can be used as a baseline to inform future studies. Generally, all analyses showed overlapping results for habitat use comparisons between the seven principal species. The primary difference between most species was temperature, with a cold-temperature assemblage that included the spiny and smooth dogfishes as well as the cownose ray, and a warm-temperature assemblage that included the Atlantic sharpnose, blacknose, and blacktip sharks, and the south- ern stingray. Apparent habitat selection was relatively similar among species within each assemblage, suggesting that the generally low spatial overlap between species may reflect behavior rather than environmental preferences. Spiny dogfish had the highest affinity for cooler temperatures and occurred -pri marily in the first half of the survey period. This pattern is somewhat consistent with the seasonal presence of this species in the southeastern US (Stehlik 2007, Ulrich et al. 2007), though spiny dogfish in Back and Core Sounds occurred at higher tem- peratures and later in the year than previously recorded (Bangley and Rulifson 2014). Smooth dogfish also occurred primarily at lower temperatures, though juveniles Table 5. Catch per unit effort (CPUE, sharks per set) by diel time period for principal elasmobranch species captured during fishery-indpendent sampling within Back and Core Sounds, North Carolina, with analysis of variance (ANOVA) results testing significance of differences in CPUE between time periods.
ANOVA Species Day Night Twilight F P df Atlantic sharpnose shark 0.12 0.14 0.23 0.80 0.45 2 Blacknose shark 0.03 0.23 0.06 4.83 0.01 2 Blacktip shark 0.03 0.09 0.00 1.64 0.20 2 Cownose ray 0.06 0.00 0.06 0.40 0.67 2 Smooth dogfish 0.03 0.00 0.10 1.18 0.31 2 Southern stingray 0.10 0.32 0.08 2.05 0.13 2 Spiny dogfish 0.20 0.00 0.17 0.22 0.80 2 Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 331
Table 6. Watson’s two sample test results comparing mean set time (hrs) for principal elasmobranch species with overall mean sampling time in Back and Core Sounds.
Species Mean set time (SD) U2 P Atlantic sharpnose shark 16:32 (0:59) 0.10 >0.100 Blacknose shark 19:08 (0:42) 0.12 >0.100 Blacktip shark 15:54 (0:59) 0.06 >0.100 Cownose ray 15:32 (0:44) 0.12 >0.100 Smooth dogfish 17:38 (0:41) 0.17 <0.100 Southern stingray 17:06 (0:52) 0.06 >0.100 Spiny dogfish 17:23 (0:28) 0.86 <0.001 were sporadically captured throughout the survey season. This closely matches observations from Bulls Bay, South Carolina, where adult females leave the estu- ary as the water warms but may give birth before migrating north (Castro 1993). The appearance of both adults and juveniles coincides with the timing of parturition in confirmed nurseries to the north (Rountree and Able 1996) and could indicate that Back and Core Sounds function as nursery habitat at the southern extent of the smooth dogfish range. These two species, particularly the spiny dogfish, are likely the dominant shark species in the estuary during cooler months. Spiny and smooth dogfish may serve similar trophic roles during the winter to small and juvenile sharks present during the summer, and may be important predators during times of year when other piscivores are rare (Grabowski et al. 2005). Further sampling during win- ter should be conducted to assess the role of these species in the dynamics of this estuary. The clearest evidence for resource partitioning occurred between blacknose and blacktip sharks, which never co-occurred in survey sets, but had no significant differ- ences in habitat variables other than inlet distance. Blacknose sharks were captured much closer to inlets than blacktip sharks, which is consistent with shark survey results from South Carolina, where blacknose sharks within estuarine waters were captured only in close proximity to inlets (Ulrich et al. 2007). However, blacktip sharks show a preference for proximity to inlets in other estuaries, particularly those with a wide salinity range (Froeschke et al. 2010). Back and Core Sounds have rela- tively low freshwater input, and most salinity measurements taken during sampling were within the ranges in which both species have been observed in South Carolina waters (13–38) (Ulrich et al. 2007). This may indicate that sharks are not spatial- ly constrained by salinity in this system. The difference in inlet distance between
Table 7. Watson’s two-sample test of heterogeneity results (U2) determining difference in mean set time between the seven principal species captured in Back and Core Sounds, North Carolina. Atl = Atlantic. Asterisks indicate statistical significance.
Atl sharpnose Blacknose Blacktip Cownose Smooth Southern Spiny Species shark shark shark ray dogfish stingray dogfish Atl sharpnose shark - Blacknose shark 0.092 - Blacktip shark 0.062 0.078 - Cownose ray 0.097 0.100 0.100 - Smooth dogfish 0.117 0.155* 0.136 0.262* - Southern stingray 0.067 0.085 0.077 0.107 0.135 - Spiny dogfish 0.485* 0.324* 0.270* 0.400* 0.403* 0.469* - 332 Bulletin of Marine Science. Vol 93, No 2. 2017
Table 8. Analysis of variance (ANOVA) results showing significant differences in environmental and spatial habitat variables between principal elasmobranch species sampled in Back Sound, North Carolina, with Tukey’s honestly significant difference grouping letters. DO = dissolved oxygen, SAV = submerged aquatic vegetation.
ANOVA/Tukey results Depth Temperature Salinity DO Inlet distance SAV distance F 1.769 42.604 7.56 5.720 3.187 5.672 P 0.11 <0.0001 <0.0001 <0.0001 0.006 <0.0001 Atlantic sharpnose shark A AB BC B AB AB Blacknose shark A AB AB AB B A Blacktip shark A A BC B A ABC Cownose ray A B C AB AB BC Smooth dogfish A C AB AB AB ABC Southern stingray A AB BC A AB AB Spiny dogfish A C A B AB C the two species may represent spatial resource partitioning between similarly-sized adult blacknose sharks and juvenile blacktip sharks. Though diet studies specific to North Carolina waters are lacking, data from other locations suggest a relatively high trophic overlap between blacknose sharks and juvenile blacktip sharks, with an em- phasis on sciaenid and clupeid fishes in the diet of both species (Castro 1996, Bethea et al. 2004, Ford 2012). The Atlantic sharpnose shark proved to be a generalist with habitat preferences that overlapped all of the principal species, and was captured concurrently at least once with every species except the cownose ray. Atlantic sharpnose sharks co-oc- curred with blacknose, blacktip, and sandbar sharks large enough (>900 mm TL) to be a predatory threat, and one blacktip shark was captured while attempting to prey on a small juvenile. Typically, juvenile sharks are thought to prioritize predator avoidance over foraging opportunities in estuarine habitats (Bush and Holland 2002, Heupel and Hueter 2002). This behavior suggests that Atlantic sharpnose sharks, particularly the young-of-year juveniles that were nearly ubiquitous in the estuary during the summer months, should select habitat that minimizes their potential to encounter larger shark species. This apparent mismatch may be explained by the relationship between life history and risk tolerance that occurs in some teleosts, in which shorter-lived, faster-growing species are more likely to risk predation to increase foraging opportunities (Frid et al. 2012). Atlantic sharpnose sharks grow relatively rapidly compared to most of the other shark species present in this estuary (Loefer and Sedberry 2003), and habitat use patterns observed in the northern Gulf of Mexico also show an apparent lack of predator avoidance (Carlson et al. 2008). The Atlantic sharpnose sharks present in Back and Core Sounds appear to follow a similar strategy, occurring across a wide variety of habitats to increase foraging opportunities. Few studies on elasmobranch habitat use include detailed information on batoids. Cownose rays appeared to select for mid-range temperatures (approximately 25.5 °C) that occurred primarily during the spring and fall, which matches observations of mass migrations of this species through Back and Core Sounds during these seasons (Peterson et al. 2001, Goodman et al. 2011). Though cownose rays had little habitat or spatial overlap with the other principal species, bullnose rays (Myliobatis freminvil- lei Lesueur, 1824) were often captured concurrently with them. Southern stingrays, like Atlantic sharpnose sharks, showed highly generalist habitat preferences though Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 333 captures of this species primarily occurred at warmer temperatures. Other stud- ies of southern stingray habitat use show that this species tends to move between habitat patches (Tilley et al. 2013) and their foraging habits may be more associated with tidal cycles than temporal or environmental factors (Gilliam and Sullivan 1993). Patterns of habitat use by other ray species with morphology and ecology similar to southern stingrays are influenced by the presence of predators, particularly large sharks (Vaudo and Heithaus 2013). The abundance of southern stingray in Back and Core Sounds may make them an ideal model species for studying habitat use changes in response to predation risk in this estuary. Data on temporal habitat partitioning showed evidence for diel specialization in the blacknose shark, smooth dogfish, and spiny dogfish. The blacknose shark ap- peared to be nocturnal based on its significantly higher CPUE at night, though Watson two-sample test results were below the critical values for significance. Mean set time differed significantly from smooth and spiny dogfish, the two species that differed significantly in mean set time from the overall sampling range. Evidence for nocturnal habitat use is in contrast to the findings of Driggers et al. (2012), who captured blacknose sharks throughout the 24-hr diel cycle. Blacknose sharks may be temporal generalists in coastal ocean nearshore habitats, but may enter estuaries primarily at night. Currently no published studies focusing on diel estuarine habitat use by this species exist for comparison. The spiny dogfish showed a strong affinity for mid-afternoon, and a less strong but significant preference for mid-afternoon was also found for the smooth dogfish. These species are known to form aggrega- tions (Rountree and Able 1996, Stehlik 2007), and significant differences in set time from other species may be a result of high numbers captured in individual sets dur- ing mid-afternoon hours rather than a true diel temporal pattern. Most sampling occurred during afternoon and evening hours, but Watson’s two-sample test results were able to distinguish mean set time for some species from the diel sampling range. However, focusing on afternoon-evening hours may have under-sampled species that appeared to be more active before noon or after midnight, such as bonnethead sharks and bullnose rays. Future efforts should attempt to sample equally during the entire 24-hr diel cycle. The use of multiple gear types allowed us to document a variety of elasmobranch species. Total elasmobranch catches did not differ significantly between gillnet and longline sets, which allowed for standardization of CPUE across gears as sharks per set, but species selectivity obviously varied by gear type. Drumline catches were lim- ited to a maximum of one shark per set and only accounted for two sharks in the entire survey, but this gear was capable of capturing the largest sharks and so pro- vided valuable data that would have been unavailable from gillnet and longline sam- pling done. Rod-and-reel gear also contributed a low number of catches, but could be used at sites near inlets or in areas of high boat traffic, allowing us to sample in locations and under conditions where deployment of other gears would have been unsafe. Use and analysis of catch across multiple gear types is a common practice in elasmobranch surveys, which often standardize catch in terms of number of sharks caught or sharks per set (e.g., Hueter and Tyminski 2007, Ulrich et al. 2007, Taylor and Bennett 2013). However, differences in catchability between gear types should always be acknowledged and assessed. Use of multiple bait types is relatively common in shark surveys (McCandless et al. 2007, Belcher and Jennings 2009). However, bait type can influence the catchability 334 Bulletin of Marine Science. Vol 93, No 2. 2017 of sharks in longline and drumline gear, both in terms of total catch and species or demographic composition (Heithaus et al. 2007, Belcher and Jennings 2009, Foster et al. 2012). Most sharks captured during the survey had relatively generalist diets (Rountree and Able 1996, Cortés 1999, Bethea et al. 2004, Shaw et al. 2016) so the po- tential effects of bait type on catch composition may have been limited, though this was not directly tested. Specialist feeders such as bonnethead (Cortés et al. 1996) and finetooth sharks Carcharhinus[ isodon (Müller and Henle, 1839)] (Bethea et al. 2004) may be under-sampled by baited gears (e.g., Ulrich et al. 2007), which was a justifica- tion for including gillnet gear in our survey. Bait type used in longline and drumline gear should be recorded during future survey seasons to determine whether it was a significant influence on catch rates and species composition in this estuary. Overall, elasmobranchs in Back and Core Sounds were spatial and temporal gen- eralists, occurring throughout the estuary wherever and whenever environmental conditions allowed, with strongest evidence for spatial resource partitioning only found between similarly-sized blacknose and blacktip sharks. Temperature was the primary abiotic factor differing between species, though this environmental factor appeared to account more for differences between elasmobranch assemblages than between species occupying the estuary at the same time. Other studies have shown temperature to more strongly affect large-scale presence or absence of elasmobranch species within a particular area, while other factors, such as salinity or dissolved oxy- gen, are a greater influence on habitat use at finer scales within the system (Grubbs and Musick 2007, Froeschke et al. 2010, Schlaff et al. 2014, Ward-Paige et al. 2015). Salinity in Back and Core Sounds was more strongly influenced by periods of heavy rainfall than consistent freshwater input, so was not limited in any particular part of the survey area. Without spatial habitat limitation by abiotic factors, elasmobranchs in this sys- tem are highly mobile and likely utilize multiple habitat types and spatial regions throughout the estuary. Use of multiple habitat types over a broad spatial area is a common tactic for mobile estuarine predators and has been previously documented for some of the elasmobranch species in this study (Heupel and Hueter 2002, Collins et al. 2007, Carlson et al. 2008, Tilley et al. 2013, Drymon et al. 2014), as well as other mobile species such as red drum [Sciaenops ocellatus (Linneaus, 1766)] (Fodrie et al. 2015). The highly mobile nature of elasmobranchs combined with the lack of limitation by abiotic factors suggests that biotic factors, such as predation risk, re- source partitioning, or prey availability, may exert a stronger influence on patterns of habitat use within Back and Core Sounds. Resource partitioning is evident in the estuarine-scale spatial partitioning between blacknose and blacktip sharks, but this may be only one example. Further sampling focusing on the use of certain habitat types at different spatial and temporal scales may reveal more evidence of interspe- cific interactions and their effects. Knowledge of elasmobranch habitat use in estuaries, especially in the context of potential interactions with other species, will help illuminate the ecological impor- tance of sharks and rays in coastal ecosystems. This knowledge is essential in manag- ing fisheries and coastal development at an ecosystem level. Bangley and Rulifson: Habitat partitioning in a North Carolina elasmobranch community 335
Acknowledgments
This research was supported by North Carolina Sea Grant Minigrant MG-1513 and depart- mental funds from the East Carolina University Institute for Coastal Science and Policy. All animal use procedures followed Animal Use Protocol D306 and subsequent amendments as approved by the ECU Institutional Animal Care and Use Committee. Survey efforts would not have been possible without dozens of volunteer field assistants, especially C Krahforst, M Rose, E McDonald, DJ Evans, D Lichti, and S Lichti. We also thank A Read at the Duke University Marine Laboratory for loaning drumline gear.
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