Aggregation of the northern abalone Haliotis kamtschatkana with respect to sex and spawning condition.
Abalones (Identification and classification)
Animal marking (Methods)
Seamone, C. Brenton
Boulding, Elizabeth G.
|Publication:||Name: Journal of Shellfish Research Publisher: National Shellfisheries Association, Inc. Audience: Academic Format: Magazine/Journal Subject: Biological sciences; Zoology and wildlife conservation Copyright: COPYRIGHT 2011 National Shellfisheries Association, Inc. ISSN: 0730-8000|
|Issue:||Date: Dec, 2011 Source Volume: 30 Source Issue: 3|
|Geographic:||Geographic Scope: Canada Geographic Code: 1CANA Canada|
ABSTRACT Current low densities of the northern abalone Haliotis
kamtschatkana may be affecting the fertilization success of this
endangered broadcast spawner, thus preventing its populations from
recovering to historical levels. This study attempted to determine
whether the northern abalone were significantly aggregated during the
period just before spawning because this may compensate in part for
their low densities. We used scuba to map the spatial distribution, sex,
and spawning condition of tagged abalone within grids at three different
sites close to Bamfield Marine Sciences Center on the west coast of
Canada. Underwater tagging methods were then used to monitor individuals
over a 3-wk period during the 2009 spawning season. We found that the
populations at all sites had nearest neighbor R ratios significantly
less than 1.0, which indicates an aggregated distribution. Within the
range of densities observed for our 3 sites (0.12-0.64
adults/[m.sup.2]), the mean distances to the nearest neighbor (1) of
either sex, (2) of the opposite sex, and (3) of the opposite sex with
ripe gonads were always less than 1.00 m except in one case. Individual
abalone aggregated independently of sex; therefore, the probability of
finding both a ripe male and a ripe female within an aggregation
increased linearly with density. We estimated that the northern abalone
populations observed were sufficiently aggregated to make successful
fertilization more likely at low densities. This is the first study to
map abalone sex and degree of gonad development that allow the analysis
of nearest neighbor measurements with respect to gender and spawning
KEY WORDS: abalone, Haliotis kamtschatkana, Allee effect, broadcast spawner, fertilization, free spawner, density, distance methods, nearest neighbor, recruitment overfishing
Mechanisms that ensure successful fertilization in a fluid environment are an important agent of selection on the reproductive behavior of free-spawning marine invertebrates. Natural spawning events are rarely observed for temperate invertebrates. Documented adaptations in echinoderms include adult aggregation behavior, spawning from an elevated position, induced synchronous spawning by both sexes, and mass spawning events induced by environmental cues, all of which result in a high local density of gametes from both sexes (reviewed by Himmelman et al. (2008)). Synchronous spawning by aggregated adults has also been observed for the northern abalone, a benthic gastropod in the genus Haliotis (Breen & Adkins 1980).
Free-spawning invertebrate populations that have been harvested to below a critical density may experience low fertilization success, which can cause the collapse of commercial fisheries. At low densities, the distances between potential mates become very large, and therefore the probability of fertilization becomes minimal (Levitan 1995, Lundquist & Botsford 2004). This inverse density dependence is known as the Allee effect (Allee 1931) and has been shown to be an important factor in a variety of free-spawning marine invertebrates, including sea urchins (Quinn et al. 1993), scallops (Caddy 1988), and giant clams (Munro 1993). The Allee effect on fertilization success is suspected to be responsible for historical patterns of commercial abalone fisheries typically showing high initial landings followed by stock declines (Sloan & Breen 1988, Shepherd et al. 2001). Button (2008) applied distance-based methods to reveal the relationship between density, nearest neighbor distances, and aggregation sizes for pink abalone (Haliotis corrugata) and red abalone (Haliotis rufescens) in Southern California. She found that the number of individuals within a 2.5-m radius aggregation decreases linearly as the population density decreases, and consequently the probability that males and females will both be present in an aggregation is greatly reduced.
The fertilization biology of various abalone species has been studied using laboratory and field studies, and computer simulation modeling (Babcock & Keesing 1999, Zhang 2008). These studies support the hypothesis that population density also plays a central role in abalone fertilization biology. For example, in South Australia, populations of Haliotis laevigata demonstrate recruitment failure when densities fall to less than 0.3 animals/[m.sup.2] or fall below a critical mean nearest neighbor distance of about 1 m (Babcock & Keesing 1999). Shepherd and Partington (1995) used a classic Ricker curve to suggest that H. laevigata from collapsing harvested populations would fail to recruit below a density of 0.15-0.2 adults/[m.sup.2]. This suggests that measuring parameters such as density, abundance, and degree of aggregation may be relevant to understanding the recruitment success of abalone species.
Decreased abalone population density may reduce fertilization success because abalone sperm is only viable for a short time after it is released into the water column. Zhang (2008) used a computer simulation model to study the parameters of fertilization across various Haliotis species, and found that fertilization success is strongly dependent on the longevity of sperm. H. laevigata eggs that are up to 2 h old show little to no signs of aging; however, sperm cells have been shown to deteriorate rapidly as a result of the respiratory dilution effect, which causes high rates of energy consumption to occur after the sperm are diluted in seawater (Babcock & Keesing 1999). Red abalone (H. rufescens) sperm detect a waterborne chemical cue, L-tryptophan, that is released by conspecific eggs less than 80 min old, and change their swimming behavior to increase the likelihood of fertilization success (Kruget al. 2009). Fertilization success peaks when red abalone sperm encounter eggs while being transported within a laminar (or viscous) shear flow of no more than 0.1 m/sec, but is reduced at higher flows (Riffell & Zimmer 1997). Populations at higher aggregation densities are therefore predicted to have more successful fertilization of gametes because the gametes are released in closer proximity to one another (Riffell & Zimmer 1997). Consequently, the egg and sperm are more likely to contact each other before the sperm deteriorates.
The northern abalone Haliotis kamtschatkana (Jonas 1845) was once widespread in shallow subtidal coastal ecosystems of British Columbia (BC), Canada: however, its populations are now devastated as a result of recruitment overfishing (Jamieson 2001). The significant declines have led to the complete closure of the BC fishery for the northern abalone in 1990. Unfortunately, the closure has not yet resulted in recovery of BC populations (Zhang et al. 2007) and the species was listed as endangered in 2009 (http://www.cosewic.gc.ca/eng/sct7/sct7_3_13_e.cfm). It is believed that the lack of recovery in BC is largely a result of low population densities that reduce spawning efficiency resulting from sperm limitation (Campbell 2000), although there are few data to support this. Recruitment failure of northern abalone in the San Juan Islands has been attributed to an Allee effect in which low population densities prevent successful spawning, as was supported by a decline in the relative abundance of juvenile abalone (Rothaus et al. 2008). Illegal fishing may also contribute to the failure of populations to recover to historical levels of abundance (Jamieson 2001).
The current study mapped the location of adult northern abalone of different sizes, sexes, and gonadal ripeness indices at three sites near Bamfield, BC, Canada. Our hypothesis was that northern abalone in ripe spawning condition would be aggregated at a scale so that nearest neighbor distances would be less than the critical distance of 1 m (Babcock & Keesing 1999) because this would enhance their fertilization success.
MATERIALS AND METHODS
The field research focused on a 1-km section of coastline in Barkley Sound, BC, including Scott's Bay and Aguilar Point (48o49' N, 124049' W). This area is known to have high densities of abalone relative to the rest of Barkley Sound in part because of its close proximity to the Bamfield Marine Science Center (BMSC), which discourages poaching. Three sites, located between Scott's Bay and Aguilar Point, were monitored over a 3-wk period in June and July. Two surveys took place at each site: the second set of surveys followed 10 days after the first set.
We divided the 1 km of coastline into 100, 10-m-long segments and randomly chose three sites. Each site consisted of a 50-[m.sup.2] area (10 x 5 m), where the long dimension was parallel to the shoreline. The depths, standardized by the Canadian Hydrographical Services 0.0-m datum, extended from 2 m down to no more than I0 m because few adult abalone are found below this depth (Sloan & Breen 1988). The perimeter of the sites was marked using lengths of lead line that were graduated at a scale of 1 m. The sites were further divided into a grid of 50 1-[m.sup.2] quadrats during each survey. A transect line was used to guide the placement of the 1-[m.sup.2] quadrat, and the precision of the quadrat was enhanced to 0.1 m on both axes using a network of fishing line, which allowed us to assign accurate grid reference coordinates to each abalone observed within the 50-[m.sup.2] area.
The goal for our first set of surveys was first to record the grid reference coordinate for each abalone observed, then to remove the individual from the substrate to tag, measure shell length, and analyze the gonads for sex and maturity. Because juvenile abalone are elusive during daylight hours (Zhang et al. 2007), only adult abalone larger than 50 mm were analyzed in our surveys. We used the location data from the first set of surveys to plot the position of each abalone within its respective digital grid. We then labeled the points with its tag number, sex, and degree of gonadal development. All tagging took place underwater using Z-spar epoxy (KOP-COAT Inc.) and special plastic abalone tags. We cut the tags (2 x 10 x 10 mm) tags from a rigid plastic and defined each by a flexible numbered tag (Hallprint Pty Ltd) that was secured to the surface with Instant Krazy glue. The shell was abraded at a position opposite from the respiratory holes and just beneath the apex. The tags were then embedded in the epoxy on the abraded area. The abalone were sexed based on gonad color: male gonads appear milky white and female gonads appear greenish brown (Fallu 1991 ). The degree of development of the gonads was also assessed using a score on a 3-point scale. Gonads that appeared to be concave and sucked into the mantle cavity were considered 1 point, gonads that were level with the lip of the shell were considered 2 points, and gonads that were convex, expanding above the lip of the shell, were considered 3 points. Spawning of the northern abalone is possible alter the gonads reach a state of 1.5 points, and the presence of a spawning abalone induces nearby ripe northern abalone to spawn (D. Richards, BHCAP hatchery, pers. comm.). Each abalone was returned to its original location after it was analyzed.
The goal for the second set of surveys was to locate the previously tagged abalone, rerecord their location, and assess the habitat at each site. The coordinates of the resighted abalone were observed, recorded, and then later plotted within the digital grid as an attempt to show any trends in abalone migration. Migrations outside the original sampling grid were also recorded. The habitat for each site was then quantified using methods derived from Lessard et al. (2007).
Distance-based methods were applied to data from our first set of surveys to quantify the spatial distributions of abalone within each study site. For each abalone within the grid, we measured the shortest distance to its nearest neighboring abalone that was also in the grid. All distances were measured digitally using ImageJ. The mean distances for the true nearest neighbor, nearest neighbor of opposite sex (OS), and nearest neighbor of opposite sex with ripe gonads (OSRG) were calculated based on the true grid reference coordinates that we recorded during our first survey. The nearest neighbor R ratio aggregation index (Clark & Evans 1954) was calculated to identify the distribution patterns to reveal whether the populations tended to fit an aggregated, random, or uniform distribution (Krebs 1999).
We also used the T-square distance-based method, as has been used extensively by Button (2008) on large-scale abalone surveys in California, to determine the site densities, mean nearest neighbor distances, and number of individuals within a 1.00-m and 2.50-m radius from randomly chosen points, which were at least 1 m from any of the grid boundaries. We generated the same number of random points as the number of abalone within the grid, and then discarded those points within a 1-m "border" of the grid edges. We then recorded the first distance measurement, x: the distance from a random point to the nearest northern abalone. The T-square procedure also requires a second distance measurement, y: the distance from that focal abalone to its nearest neighboring abalone within the perimeter of a half circle, with its diameter bisecting the focal individual but perpendicular to and extending away from a vector that connects that individual to the initial random point (for further details see Button (2008)). A third distance measurement, z. was not always equal to v because sometimes the nearest neighbor was found on a half circle extending toward the initial point.
To test whether the abalone were aggregated with respect to the OS during our first set of surveys, a bootstrap loop, using the actual empirical nearest neighbor distances, was generated by an R-computer language script written by Dr. B. Anholt. This allowed us to yield an expected distribution of the nearest neighbor distances between potential abalone mates at each site. This was done by modeling digital grids and populating them with individuals randomly distributed with respect to gender. The nearest neighbor of the OS was determined for each simulated abalone, and was averaged for males and for females. If natural abalone populations exhibit nearest neighbor distances closer to a potential mate than expected by chance, the mean of the observed data will fall within the 95% confidence limits of the mean of the randomly generated distribution. The bootstrap loop was executed 1,000 times for each site, and allowed us to test whether male or female abalone were more likely to be near an abalone of the OS rather than what was expected by chance.
[FIGURE 1 OMITTED]
To determine whether shell length and or habitat dissimilarities were potentially correlated with abalone distribution data from our first set of surveys, two additional tests were used. ANOVA (general linear model module of SPSS version 18.0) was used to compare the shell lengths of the abalone of different sexes at the three sites. The interaction between sex and site was not significant (P = 0.776), so it was removed from the final model. We also used the "Table" procedure to compare the proportion of ripe abalone of different sexes at the three different sites. SIMPER analysis was run in Primer Statistics (Clarke & Gorley 2006) to determine the similarity or dissimilarity between the abiotic and biotic habitat features found at each of our 3 study sites, which allowed us to relate abalone density to habitat features. Last, to reveal potential differences among sites, the index of gonadal development was analyzed as a function of shell length for all abalone tagged at all three sites.
Although northern abalone density varied among the three sites, each site population had significantly aggregated distributions. In addition, average nearest neighbor distances were sufficiently short to allow for successful spawning. The summary statistics for site density (Table 1) show that sites 1, 2, and 3 were ranked in the same order--as the lowest, intermediate-, and highest density sites, respectively--whether we used true quadrat density or T-square density. The T-square density tended to overestimate the true density; however, the z test statistic showed that the two measures were not significantly different (Table 1).
The nonlinear regression analysis showed that true density only explained 52% of mean nearest neighbor distance (y = 0.3284[x.sup.-0.10] + 0.1612, [R.sup.2] = 0.5227, P = 0.48, n = 3). None of the three mean nearest neighbor measurements, whether derived from the true grid reference coordinates or estimated with the T-square method, differed significantly among sites (Fig. 1). The mean values fell below 1.00 m in every instance except for mean distance to OSRG at site 2. which was 1.31 m for the grid method (Fig. 1A) and 1.22 m for the T-square method (Fig. 1B).
[FIGURE 2 OMITTED]
The nearest neighbor R ratios revealed significantly aggregated distributions at all three sites with respect to the nearest neighbor (Table 2). However, the nearest neighbor OS R ratio for males at site 3 and the nearest neighbor OS R ratio for females at site 1 were not significantly different from the null hypothesis of a random distribution (Table 2).
[FIGURE 3 OMITTED]
The randomized distribution results show that H. kamtschatkana aggregated randomly with respect to sex at our medium- and high-density sites 2 and 3 (Fig. 2). The randomization analysis revealed that at sites 2 and 3, the mean distances to the nearest neighbor of the OS fell within the 95% confidence limits of the randomized distribution generated from the data, and therefore did not show significant deviations from a random distribution. However, at our lowest density site (site 1), the mean distance to the nearest neighbor OS for males was significantly less than expected by chance, suggesting a tendency for the animals to aggregate around the single individual female that was present in the grid (Fig. 2A).
The number of H. kamtschatkana individuals aggregated within a 1.00-m and 2.50-m radius from a central individual tended to increase linearly with density (Fig. 3), but the trend was not significant with only three data points. As density increased, the number of northern abalone within an aggregation became larger, and the probability of both males and females being present in an aggregation increased (Table 3). The probability that there was at least H. kamtschatkana of the OS within a 1.00-m radius was only moderate (site 1, 0.50; site 2, 0.63; site 3, 0.84). However, the probability of an individual of the OS within a 2.50-m radius was high for all sites (Table 3).
Migration distances for resighted individuals increased in congruence with site density. The averaged migration distance was 1.53 m, 2.92 m, and 4.14 m at sites 1, 2. and 3, respectively, and the maximum migration distance observed was more than 8 m (Fig. 4). Many resighted individuals were found outside the grid boundary, and several untagged individuals had migrated to within the grid boundaries.
ANOVA showed that the mean size of the abalone tagged was significantly larger at site 2 than at site 3 (Table 1; Tukey test, P = 0.02). However, there was no difference in the mean size of males and females (Tukey test, P = 0.18). The proportion of abalone with ripe gonads was not significantly different between sites 2 and 3 (chi-square, P = 0.208), so all data were combined. The histogram of the gonad ripeness index as a function of shell length and sex for all three sites combined showed that all abalone larger than 55 mm contained some ripe individuals, with an index greater than 1.5 (Fig. 5). However, no individuals of either sex reached the maximum ripeness index of 3.
[FIGURE 4 OMITTED]
[FIGURE 5 OMITTED]
The SIMPER analysis for habitat similarity showed that all three sites shared common features but in different proportions (Table 4). Sites 2 and 3 were most similar (81.54%) and sites 1 and 3 were the least similar (74.16%). Across the three sites, the abundance of abalone increased with the abundance of boulders and also with the abundance of bedrock containing crevices. Surprisingly, the sunflower star, Pycnopodia helioanthoides, was most abundant at site 3, which also had the highest density of abalone.
The survey data supported our hypothesis that northern abalone, in ripe spawning condition, would be aggregated at a scale so that nearest neighbor distances would be less than the critical distance of 1 m, and this would enhance their fertilization success (Babcock & Keesing 1999). The mean nearest neighbor distances were less than 1.00 m at all sites. The nearest neighbor distances that we observed for the aggregated populations at sites 2 (R ratio = 0.8) and 3 (R ratio = 0.8) were only 80% as large as would be expected for a randomly distributed population of the same density (Clark & Evans 1954). The nearest neighbor distance at site 1 compensated in part for a population density (0.12 adults/[m.sup.2]) that was less than that recommended ([greater than or equal to] 0.32 adults/[m.sup.2]) for species recovery (Lessard et al. 2007) that was based by fitting a Beverton-Holt model to time-series data from abalone survey index areas (Zhang et al. 2007).
Our studied populations may exhibit spawning aggregation behavior as described by Breen and Adkins (1980) to allow for successful spawning events. The probability of fertilization in free-spawning populations is largely dependent on the mean nearest neighbor distances between individuals (Levitan 1991, Babcock & Keesing 1999), rather than the true density. Zhang's (2008) fertilization model assumes that spawning aggregations always result in an R ratio = 0.5 which indicates that nearest neighbors are only half as far away as expected under a random distribution. His Fig. 3 predicts that aggregation will increase the fertilization success by less than 5% at our two higher density sites and by 12% at our low-density site. However, his model may underestimate the importance of aggregation particularly at our low density site where the R ratio = 0.4.
Our study shows that successful spawning is possible even at site 1, where the average density is only 0.1/[m.sup.2], because aggregation creates patches with nearest neighbor distances less than 1 m. The abalone sampled at site 1 seemed to be concentrated on a small piece of flat bedrock that was well above the surrounding terrain. However, grid size limitations must be considered because the periphery of site 1 was observed to bisect the aggregation on this high point. Resighted individuals that had been tagged within site 1 usually had migrated outside the site grid periphery, suggesting that the edges of the aggregation extended beyond the site boundary (Fig. 4). As a result, the density calculation at site 1 may be a low estimate of the true aggregation density. Alternately, the high abundance of sea urchins at site 1 may contribute to reduced abalone population densities as urchins are known to compete for habitat with adult abalone (Sloan & Breen 1988).
This study is the first to map the sex and degree of gonad development of individual abalone, thus allowing us to analyze the spatial distribution with respect to gender and spawning condition. If adult H. kamtschatkana do occur in a sex ratio of 1:1 (Sloan & Breen 1988), then sex-based nearest neighbor measurements such as the nearest neighbor of OS and nearest neighbor of OSRG may be important to determine whether the mixed gender is spatially oriented to allow spawning success. The results of our study show that there was no instance in which the estimate of OS and OSRG was significantly greater than 1.00 m (Fig. 1). The males at site 1 showed preferential aggregation (OS) around the single female present (Figs. 2 and 4); however, this could also be explained if all individuals aggregated in the few patches of suitable habitat.
The tagging of individual abalone at each site during the initial surveys allowed us to observe a high rate of migration within the H. kamtschatkana populations during this study. These migrations may be explained by Breen & Adkins (1980), who described high activity of H. kamtschatkana as the individuals prepared for a spawning event. These migrations may also be the result of an alarm response initiated by abalone when they become disturbed or are under threat of predation (Cook 1992). During the surveys, the abalone were observed to exude a mucuslike substance regularly after they were removed from the substrate by touching them with a sunflower sea star (P. helioanthoides) arm (C. B. Seamone, pers. obs.). Cook (1992) has shown that this substance initiates an alarm response that results in agitated running behavior. A third possible explanation for the migration is that the abalone were in search of food. The abundances of the preferred food for adult northern abalone--bull kelp and giant brown kelp--was low in each of the chosen study sites (Sloan & Breen 1988).
Recruitment overfishing of H. kamtschatkana on the coast of BC has contributed to the high rate of stock declines (Jamieson 2001). The relatively healthy populations of northern abalone within Scott's Bay and Aguilar Point, where little poaching occurs, have commenced an understanding of the distribution of this species with regard to aggregation that may prove to be beneficial for future stock management. These populations display a strong tendency toward aggregated distributions, with most R ratios significantly less than 1.0, and most mean distances for nearest neighbor, nearest neighbor OS, and nearest neighbor OSRG were less than 1.00 m. Thus, these data support our hypothesis that H. kamtschatkana populations aggregate at a scale of 1 m during the spawning season to enhance their fertilization success. We cannot, however, exclude the possibility that the aggregation that we detected results from habitat selection by the abalone rather than by active aggregation behavior by abalone with ripe gonads.
The aggregated distribution at our sites gave only moderate probabilities of finding a male and female within the 1.00-m radius that gives a predicted fertilization success greater than 70% (based on H. laevigata (Babcock & Keesing 1999)). Future work using natural and induced in situ spawning events would allow more accurate predictions of the effects of aggregation on fertilization success by using spawning parameters specific to H. kamtschatkana. It would also be of interest to conduct studies that continually monitor the distribution of the populations at each site during the remainder of the year to determine whether it is different outside the spawning period. It is reasonable to hypothesize that outside the spawning season, the need for an aggregative distribution may subside, and the animals may increase efforts with regard to foraging and predator evasion. Last, an increase in the number of sample sites would strengthen the evidence for observed trends, because our grid size may not have encompassed the entire size range of aggregations present in this study. The continuation of this project over a longer time period with increased sample sites would likely produce concrete trends that could be used to analyze the effectiveness of future management and recovery programs.
We thank the director of BMSC, B. Anholt, for his assistance with the bootstrapped loop statistical analysis, as well as B. Rogers and the rest of the BMSC staff for making this project possible. We are grateful to J. Lessard for suggesting this project, and also to D. Brouwer and D. Bureau for technical suggestions; S. Shumway and two anonymous reviewers for editorial suggestions: and tan Smith for redrawing the figures. We also thank the main dive team members (P. Mitchell, J. Holsworth, S. Stone, and S. Frioult) as well as the algal survey dive team (K. Read, G. Wittig, and C. Hansen). A special thanks to L. Rogers-Bennett for discussions, and to C. Button for her generosity in giving us a copy of her PhD dissertation. Research support was from BMSC and from NSERC Strategic Grant STPSC 357084-07 (Gosselin, Boulding, Harley).
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C. BRENTON SEAMONE (1) AND ELIZABETH G. BOULDING (1,2)*
(1) Bamfield Marine Sciences Centre, Bamfield, BC, V0R 1B0, Canada; (2) Integrative Biology, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
* Corresponding author. E-mail: email@example.com
TABLE 1. Number and shell length (measured in centimeters) of abalone tagged (n), true densities, T-square density, and the z statistic comparing the two density estimates for all three sites. Shell True Density T-Square Length (no. of Density (no. Site n (SE) adults/[m.sup.2]) of adults/[m.sup.2]) 1 6 72.7 (8.625) 0.12 0.22 2 24 87.6 (3.357) 0.48 0.49 3 32 75.0 (2.940) 0.64 0.98 z Test Site Statistic P 1 -0.042 0.966 2 -0.025 0.980 3 -1.468 0.142 TABLE 2. R ratios (Clark & Evans 1954) for the true nearest neighbor (NN), and for the NN of the opposite sex (OS) calculated separately for males and females at all three sites, and the z statistic testing whether R is significantly less than 1, indicating aggregation. Site R NN z Test P R Males OS z Test P Statistic Statistic 1 0.389 -3.24 0.004 0.248 -2.87 0.004 2 0.761 -2.59 0.025 0.598 -2.55 0.011 3 0.761 -2.86 0.010 0.915 -0.68 0.497 Site R Females OS z Test P Statistic 1 0.171 -1.58 0.112 2 1.015 -3.09 0.003 3 0.645 -8.96 0.0001 TABLE 3. Number (mean [+ or -] SD) of adult abalone within a 1.00-m radius and within a 2.50-m radius, and the probability of there being at least 1 male (M) and 1 female (F) within that radius. P [greater than or equal to] 1 M n (1-m and 1 F n (2.5-m Site radius) SD (1-m radius) radius) SD 1 3.33 1.63 0.50 6.00 0.00 2 3.87 2.23 0.63 6.13 2.42 3 4.63 2.03 0.84 13.84 4.62 P [greater than or equal to] 1 M and 1 F Site (2.5-m radius) 1 1.00 2 0.87 3 0.95 TABLE 4. SIMPER analysis for habitat similarity. (A) Groups site 1 and site 2: average dissimilarity = 19.42. Site 1 Site 2 Species Abundance Abundance Average Dissimilarity Cobble 0.00 3.00 3.30 Articulated corallines 0.00 2.00 2.70 Urchins 49.00 68.00 2.38 Bedrock, crevices 1.00 0.00 1.91 Nereocvstis 0.00 1.00 1.91 Laminaria 0.00 1.00 1.91 Desmarestia 0.00 1.00 1.91 Boulders 1.00 3.00 1.40 Bedrock, smooth 4.00 2.00 1.12 Species Contributing % Cumulative Cobble 17.01 17.01 Articulated corallines 13.89 30.89 Urchins 12.24 43.13 Bedrock, crevices 9.82 52.95 Nereocvstis 9.82 62.77 Laminaria 9.82 72.59 Desmarestia 9.82 82.40 Boulders 7.19 89.59 Bedrock, smooth 5.75 95.34 Each variable is given a dissimilarity rating between sites, and the contributing percent indicates how much each variable contributes to the overall dissimilarity between sites. Only dissimilar variables are shown. (B) Groups site 1 and site 3: average dissimilarity = 25.84. Site 1 Site 3 Species Abundance Abundance Average Dissimilarity Bedrock, smooth 4.00 0.00 4.19 Urchins 49.00 29.00 3.38 Cobble 0.00 2.00 2.96 Boulders 1.00 5.00 2.59 Bedrock, crevices 1.00 0.00 2.10 Pycnopodia 1.00 4.00 2.10 Sharp-nosed crab 0.00 1.00 2.10 Desmarestia 0.00 1.00 2.10 Articulated corallines 0.00 1.00 2.10 Species Contributing % Cumulative % Bedrock, smooth 16.22 16.22 Urchins 13.10 29.32 Cobble 11.47 40.78 Boulders 10.02 50.81 Bedrock, crevices 8.11 58.92 Pycnopodia 8.11 67.03 Sharp-nosed crab 8.11 75.14 Desmarestia 8.11 83.25 Articulated corallines 8.11 91.36 Each variable is given a dissimilarity rating between sites, and the contributing percent indicates how much each variable contributes to the overall dissimilarity between sites. Only dissimilar variables are shown. (C) Groups site 2 and site 3: average dissimilarity = 18.46. Site 2 Site 3 Species Abundance Abundance Average Dissimilarity Urchins 68.00 29.00 5.23 Bedrock, smooth 2.00 0.00 2.58 Pycnopodia 1.00 4.00 1.83 Sharp-nosed crab 0.00 1.00 1.83 Nereocrslis 1.00 0.00 1.83 Laminaria 1.00 0.00 1.83 Boulders 3.00 5.00 0.92 Crushed shell 2.00 1.00 0.76 Species Contributing % Cumulative Urchins 28.32 28.32 Bedrock, smooth 14.00 42.32 Pycnopodia 9.90 52.22 Sharp-nosed crab 9.90 62.11 Nereocrslis 9.90 72.01 Laminaria 9.90 81.91 Boulders 4.99 86.90 Crushed shell 4.10 91.00 Each variable is given a dissimilarity rating between sites, and the contributing percent indicates how much each variable contributes to the overall dissimilarity between sites. Only dissimilar variables are shown.
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