I

I KELP FORESTINVERTEBRATE ECOLOGY PROJECT Department of Biological Sciences University of Southern California I Los Angeles, California 90089 I I I STUDIESOF BENTHICORGANISMS IN KELP FORESTSNEAR THE t SAN ONOFRENUCLEAR GENERATING STATION 1980 - 1986 I t FINAL REPORT

I By:

I John D. Dixon and Stephen C. Schroeter Principal Investigators I and Richard O. Smith I Research Associate Contributing Staff:

I Mark D. Con1in Troy S. Del1e Michael H. Gunnels I Tirnothy J. Herrlinger Richard B. Herrmann Joyce A. Joseph Richard L. Kotter T Charles Mann

I Submitted to the Marine Review Committee, Inc. I March 10, 1988 I TABLE OF CONTENTS

ABSTRACT 1

INTRODUCTION 2

NATURALHISTORIES OF COMMONKELP FOREST INVER?EBRATES. 4

FIELD METHODS: SURVEYSOF BENTHIC INVERTEBRATES. L4

FIELD METHODS:KELP RECRUITMENTSURVEYS. 18

DATA BASE I"IANAGEMENT 20

ANALYSIS z2

RESULTS. 30

DISCUSSIONAND CONCLUSIONS 43

ACKNOWLEDGMENTS. 45

LITERATURE CITED 47

TABLES 52

FIGURES. 72

APPENDIX A: TEST OF THE ASSI'MPTIONSUNDERLYING THE BAcrP ANALYSES '253

APPENDIX B: FLOW CHARTS OF COMPUTERPROGMMS USED TO PRODUCE THE TABLES AND FIGURES .268 I

I ABSTRACT

I The BACIP study of large benthic invertebrates began in the falI of I 1980. Ten preoperational and eight operational surveys were conducted. There was a general decline in the abundance of gastropod mollusks in I the upcoast portion of the San Onofre kelp forest after the San Onofre Nuclear Generating Station's Units ? and 3 began operating. This I pattern is particularly striking for tvro species of predatory gastropods, Conus californicus and Kelletia kelletii. The most likely

I mechanisms underlying the obse:rzed changes are changes in habitat I caused by loss of kelp and understory a1gae, and an increase in seston flux and sedimentation. One of the striking changes during the I operational period was the accumulation of a cohesive, fine sediment at the upcoast monitoring station at San Onofre. We first saw this I sediment in the fall of 1985. Its spatial distribution and the timing of its appearance suggest that it is related to the operation of SONGS

I Units 2 and 3. I I t I I I I I t

I INTRODUCTION

I Our mandate from the Marine Review Committee, Inc. (MRC) was to I conduct a study to determine whether the operation of Units 2 and 3 of the San Onofre Nuclear Generating Station (SONGS)affects populations I of large benthic invertebrates in the San Onofre kelp forest (SOK). Like most kelp forests in southern California, San Onofre contained a I diverse group of plants and animals, including hundreds of species of benthic invertebrates. Among the latter were species of sport and

I commercial importance (e.g., abalones, lobsters, sea urchins, and sea I cucumbers) , and those of functional importance in structuring the kelp bed community (e.g., sea urchins and sea stars). When considering how I to evaluate the possible impact of the discharged cooling waters on such a diverse assemblage, the first problem was to select the group of t species to study. We chose species that 1) are characteristic of kelp forests in southern California, 2) have been shown to influence the

I structure and dynamics of kelp bed communities, and 3 ) can be counted I easily by divers in the field under conditions of relatively poor visibility. Sessile invertebrates such as bryozoans, hydroids, and I sponges, which form a turf on many hard substrates, were studied by another contractor (Osmanet al 1981). I Equally important was the selection of the sites at w'rich the species were monitored. Ideally, the perturbed area and the control t areas to which it would be compared would differ only in the I perturbation. This, of course, is not possible in nature. In the vicinity of SONGSthere are only three more or less persistent kelp I forests. Besides San Onofre, there are the San Mateo kelp forest (SMI() I 2 I I

I and the Barn kelp forest (BK) (Figure 1). Despite some differences in bottom composition and relief, we chose these areas as control sites. t By using two widely spaced controls, w€ could estimate natural I variability on the scale of several kilometers. We also established two stations in the San Onofre kelp forest. The cooling waters from Units 2 I and 3 are discharged from a series of ports upcoast from the kelp bed. We placed two stations under the kelp canopy, one station as elose to I these diffuser ports as possible, and the second as fat away as possible. Wehoped to get an idea of the distance over which the cooling

I water discharge had an effect by comparing these two stations. I The experimental design was the Before-Aftetl Control-Impact-Pairs (BACIP) discussed by Stewart-Oaten (1986) and Stewart-Oaten et al I (1986). Samples were taken at approximately equal intervals before and after Units 2 and.3 began operating. For each species, the difference t in abundance between the impact and control site was calculated for each survey. If the power plant had no effect, one would expect that the

I average difference between sites would be the same after Units 2 and 3 I began operating as before. The test of this hypothesis is the subject of this report. I I I I I I I I

I NATURAL HISTORIESOF COMMONKELP FORESTINVERTEBRATES

I Perhaps the most studied denizens of kelp forests are sea urchins. I Three species of sea urchins commonly occur in the kelp beds near the San Onofre Nuclear Generating Station: Red and purple sea urchins, I Strongylocentrotus franciscanus and S. purpuratus, respectively, and white sea urchins, Lytechinus anamesus. The diadematid sea urchin, I Centrostephanus coronatus, also occurs, but is rare. Red and purple urchins occur almost exclusively on rocky substrates. White urchins

I are not only conmon on some hard substrates, but are also abundant on I sand and mud bottoms. Locally, white urchins are often most numerous in the sandy areas at the peripheries of kelp beds (Schroeter et al 1983). I Each of the three abundant urchin species is a grazet whose diet includes the giant kelp, Macrocystis pyrifera (Leighton 1950; t Boolootian and Lasker L964, cited in Lawrence L975; Leighton et aI f965). Giant kelp is the preferred food of red and purple seaurchins.

I Although opinions differ on the general importance of sea urchin t grazing to the distribution and abundance of kelp in southern California (for a discussion, see North L974), there is fairly l convincing evidence that strongylocentrotid urchins can lirnit, reduce, or eliminate kelp beds (Leighton 1968, L97L; North and Pearse L97O;

I North L974; Iearse and Hines L979; Dean et _d 1984). A change in behavior precedes destructive overgrazing by red and purple urchins

I (Leighton 1960, L97L; Leighton et al L956; Dean et al L984; Harroldand I Reed 1985) . When drift algae is abundant, it is their primary food (Irvine L973, cited in Lawrence L975). Under these conditions, the I urchins remain more or less stationary and capture the drifting algae I t I

I with their spines and tube feet (Lees L97O; Rosenthal et al L974; Mattison et al L977; Harrold and Reed 1985). However, when drift algae

I are scarce, red and purple urchins move over the substrate and graze on I attached algae (Leighton 1950, L971; Leighton et al 1966; Mattison et al L977). Since rates of movement are inversely related to the I availability of drift algae (Lees 1970), it seems likely that active grazing is stimulated by starvation. t Grazing aggregations or "fronts" of red sea urchins have occurred in both the San Onofre and San Mateo kelp beds. One urchin front

I eliminated kelp along one of the Kelp Ecology Project's (KEP) transects I in the downcoast portion of the San Onofre kelp bed in 1981 (Dean et al 1983). Another removed nearly all algae from our control site in the I San Mateo kelp forest. Fortunately, most of the grazing took place after the study was completed. t gefore about 1983, white urchins were relatively rare on shallow rocky substrates. They were usually found on soft sediments in bays or

I deepwater, or inareas just outside ofkelp forests (Morris et al 1980; I Schroeter et aI 1983). The presence of'the sea star, Asterina miniata (= Patiria miniata), and perhaps other asteroids in the kelp forest, t appeared to restrict the distribution of white urchins to peripheral areas (Schroeter et al 1983). Although high densities and destructive I grazing by L. anamesus on kelp was occasionally observe I (Clarke and Neushul 1967; personal observations), white urchins were generally an t unimportant source of kelp mortality (Leighton 1971). I This situation has recently changed. During the L982-1984 El Nino, shallow water asteroid populations were drastically reduced I throughout the southern California Bight by a series of epizootics I I I

I caused-by a bacterium of the genus Vibrio (Schroeter et a1 f988b). Concurrent with the decline in sea stars, the density of white urchins I in kelp habitats increased at sites from San Diego to Santa Barbara and

at the Channel Islands (Tegner and Dayton 1987; J. Patton, personal

I communication; unpublished data). Since L. anamesus generally have I been uncommonin kelp forests, there have been few studies of their effects on giant kelp (notably, Clarke and Neushul 1967; Leighton L97L; t Dean et al 1984), and the long-term significance of the recent change in their distribution is difficult to judge.

I Lytechinus anamesus have always been present at SOK and SMK. Our I observations and field experiments indicate that grazlng by L. anamesus can affect both recruitment of juveniles and the standing t stock of adult kelp. Using data collected from L978 to 1986, we found a significant negative correlation between urchin density and that of I kelp recruits (Schroeter et a1 1988a). lle also noted that kelp recruits were generally absent in areas of very high urchin density. In fact,

I white urchins appear to set the offshore boundary of the kelp forest at t one of olrr study sites (Dean et al 1984). We have also observed significar't grazing on adult kelp. In February 1985, large numbers of t white urchins began grazing on the holdfasts and fronds of adult plants, which resulted in heavy mortality during a period of storm waves and I associated strong surge (Dixon and Schroeter f985 ) . Grazing on adult kelp is still occurring at someof our study sites. t Eight species of sea stars were encountered in our benthic I surveys. The four most abundant were Asterina miniata, Astrometis sertulifera, Pisaster giganteus, and Dermasterias imbricata. A11 are I predators on sessile or motile invertebtates. Astrometis and I I I t Dermasterias prey on adult and juvenile purple sea urchins (Leighton L97L; Rosenthal et aL L974), and probably consume juvenile red urchins

I as well (Leighton 1971). Other prey of Astrometis that are counted in I the benthic surveys are the tunicate, Styela montereyensis, and the predatory snails, Kelletia kelletii and Conus californica (Rosenthal et I a\ L974). In addition to sea urchins, Dermasterias preys on at least two other species counted in our surveys: the solitary sPonge, Tethya I aurantia, and the sea star, Astrometis sertulifera (Rosenthal and Chess L972). Asterina miniata is an opportunist that fiIls the roles of

I herbivore and scavenger (Gerard L976). It also preys on some species of I bryozoans (Day and Osman 1981) and on white sea urchins (personal observations). In the San Onofre kelp bed, Asterina significantly I affects the distribution and abundance of white urchins (Schroeter et al 1983). Since grazing by Lytechinus appears to limit the recruitment I of juvenile kelp plants (Dean et al 1984), predation by Asterina may have an important indirect effect on the loca1 distribution and

I abundance of kelp. I A diverse assemblage of prosobranch gastropods is found in most kelp forests, including those near SONCSUnits 2 and 3. The most I abundant of these snails in the San Onofre kelp forest were the large whelk, Kelletia kelletii, the cone'she11, Conus californicus, and the I muricid, PLerryggpgrg festiva. Kelletia is a carnivorous scavenger that is often found feeding on dead or moribund individuals in company t with the sea Stars, Pisaster giganteus, Pisaster brevj-spinus r of I Dermasterias imbricata (Rosenthal L97L). Kelletia forms breeding aggregations of 15 to 20 individuals in the early spring and lays egg I capsules on 1ow relief rocky substrates (Rosenthal 1970). Each capsule I I I

I contains from about 400 to 22OOeggs. The larvae leave the capsule as swimming veligers.

I Cqnus californicus is the only memberof its primarily tropical I genus found in California waters. It is a generalist predator and a scavenger! and occurs on both hard and soft bottom substrates. In a I two-year study conducted at the Hopkins Marine Laboratory, Shaffer (1986) found that Conus migrated into the kelp forest to breed in the I late spring and early summer. Shaffer (f986) also found that cone shells selectively oviposit on the red alga, Rhodymenia pacj.fica. The

I eggs are laid in elaborate capsules that are attached to the blades of I the algae. Pteropurpura festiva occurs in intertidal as well as subtidal I habitats. In the subtidal, it often occurs on rocky substrates in bays (Mclean 1978). Wehave seen large numbers of large individuals on rocky I substrates in the Agua Hedionda lagoon about 40 km south of the San Onofre kelp forest (personal observations ) . Our knowledge of the t feeding and reproductive biology of Pteropurpura comes from studies of I intertj-dal populations near La Jo1la, California, and northern Baja California. Dietary composition varies from site to site, but consists t primarily of bivalves and snails, including other muricids (Fotheringham L97L, 1.974). Breeding in these intertidal populations I occured f rcm March thr tugh July. Pteropurpura f ormed mixed aggregations with other muricid snails. Females laid multiple egg

I capsules, each containing 500 to 600 eggs. In three to four weeks, the I larvae developed into swimming veligers and emerged from the capsules. Successful recruitment occurred in one out of the three years these t populations were studied (Fotheringham 1971) . I I I

I Two other species of muricid snails. Maxwellia gemma and Murexiel 1a santarosa!4, occur in moderate abundances in the kelp beds

I near SONGS. As is the case with other muricids, they are probably I benthic predators. We have seen large breeding aggregations of Maxwellia on cobbles and boulders at depths of about 17 meters in the t Barn kelp bed. Mitra idae, the only member of the family Mitridae along the t California coast, iS a specialized predator on the sipunculan, Phascolosoma agassizii (Fukuyama and Nybakken f983). It breeds from

I February to July in southern California, laying 100-200 elongate egg t capsules on rocks. The capsules contain from 100 to 1000 eggs. Swimming veligers emerge from the capsules after about 24 days (Morris I et al 1980). Two ubiquitous archaeogastropods, the top she1ls, Tegula I aureotincta and Calliostoma supargranosum, are fairly commonin the kelp forests near SONGS.Tegula aureotinctlr occur in the low intertidal

I and commonly in kelp forests in southern California, where they feed on I micro-algae (Schmitt f982). Little is known of their breeding behavior, but a related species, Tegula funebralis, lays small I gelatinous egg masses containing several hundred eggs on rocks in the intertidal. Settlement of srnall"snails occurs about two weeks after the I eggs are laid (Morris et al 1980). Calliostoma supragranosum and the less abundant Calliostoma

I gloriosum are commonly found on rocky substrates in kelp forests I (Mcl,ean 1978). Calliostoma gloriosum is a scavenger, and a speci-alized predator on the sponge, Xestospongia diprosopia (Perron 1975). I I t I

I Four of the most abundant sessile invertebrates are: the gorgonian cora1, Muricea californica, the solitary tunicate, Stye1a

I montereyensis, the gorgonian coral, Muricea fruticosa, and the solitary I sponge, Tethya aurantia. The two species of Muricea are characteristic of most southern California kelp beds, and in many instances contribute t substantially to the vertical structure of the understory. Both species have been studied extensively in San Diego County by Grigg

I (1970, L972, L974, L975, L977), who usedthe outfall structure of SONGS Unit I as one of his study sites (Crigg L977). Muricea californica is I almost always the more abundant of the two species, the ratio of the I maximumabundances of the two species being about 2.5:L (Grigg L977). The difference in abundance seems to be a result of the fact that I Muricea californica recruits at a rate 2-3 times that of Muricea fruticosa and lives, on average,2-3 times as long (Grigg L977). Inour I study, M. ealifornicawas the most numerous sessile species, about 3.5 times more abundant than M. fruticosa.

I The solitary tunicate, Styela montereyensis, is the second most t abundant sessile species sampled in our surveys. Although Iittle is known about its natural history, Rosenthal et a1 (L974) estimated that I Styela had a life expectancy of 12 to 20 months in a kelp bed near DeI Mar, California. Heavy reeruitment usually occurred in the late I summer, but it was balanced by heavy mortality in the late spring, and population numbers remained fairly constant (Rosenthal et qI L974).

I The orange demosponge, Tethya aurantia, iS a conspicuous I inhabitant of rocky substrates in kelp forests. It reproduces both sexually and asexually (Berquist 1978) . It is an ovipotous species I whose oocytes develop in the sea water. Within about 24 hours, a I 10 t I

I typical parenchymella larva is formed. The larvae of most sPonges swj-m for 3-48 hours before settlement (Berquist 1978). Tethya reproduces

I asexually by budding. I Several species of sport and cornmercial interest occur in local kelp beds. Abalones (HaIiotis spp.), lobsters (Panulir-us interruptus), I crabs (Cancer spp), and red sea urchins (Strongylocentrotus fraqqlrc4nqq) are all harvested. A11 occur in our study areas, but with I the exception of red sea urchins are normally too rare and too cryptic to be effectively sampled using our field protocol. Red sea urchins

I have been harvested in the San Mateo kelp bed since L977, and in the San I Onofre kelp bed since 1981. I ComparisonsWith Other Kelp Forests The species we studied are characteristic of kelp beds in southern I California. This assertion is based largely on personal observations and conversaticns with other workers, but also on a review of published

I papers and reports. In the context of comparing faunas, it is I unfortunate that most of these papers report either the results of quantitative work done on a subset of the taxa we sampled, or of less t quantitative descriptions of entire communities. An exception j.s the study of a kelp bed near Del Mar, California (approximately 70 I kilometers south of SONGS)conducted from July L967 to February L973 (Rosenthal'et aL L974) .

I These investigators sampled L4 species of conspicuous I macroinvertebrates in 95 1-rn2 quadrats in August Lg72. In addition, solitary tunicates, Styela montereyensis, and gorgonian coraIS, c I Muricea californjlq4, were sampled in 12 4-m' quadrats approximately quarterly from 1968 to L972. I t1 I I

I A major difference between the invertebrate assemblage in the De1 Mar bed and those in the beds near San Onofre was that the former was at

T times dominated by the tubiculous polychaete, Diopatra ornata. I Diopatra was at first uncommon, but eventually became the most abundant invertebrate in the bed. This species influenced the physical I structure and very likely the dynamics of this bed, since in one instance it covered 25-307" of a sampling area. Diopatra occurred, but I were uncommon in the three beds sampled in our surveys. The abundances of white sea urchins and the predatory snail, Kelletia kelletii, also

I differed between De1 Mar and the kelp beds near SONGS. White urchins I occurred at all of the sites sampled in our surveys, and were most abundant in the San Onofre kelp bed, but were not present at DeI Mar. I Kelletia were equally abundant at Del Mar and in the Barn kelp bed, but were about five times more abundant at the other beds surrounding SONGS. I Gorgonian populations at Del Mar were much larger than in the San Onofre kelp bed, buE are only one-seventh to one-third the size of populations

I in the San Mateo and Barn kelp beds. l Of the differences observed in the invertebrate assemblages of the different beds, two are of clear ecological importance. The San Mateo, I Barn, and Del Mar kelp beds had much larger popul.ations of gorgonians than the San Onofre kelp bed'. This probably reflects differences in the I stability of substrates. The Del Mar, San Mateo, and Barn kelp beds occur on shale or boulder reefs, whereas the San Onofre bed is

I essentially a cobble field interspersed with sand. Therefore, at San I Onofre the hard substrates are more prone to being turned and tumbled during periods of strong wave surge, and are subject to periodic, and I often extensive, burial. Thus, the first three beds are probably much I L2 t I

I more stable over time for rocky bottom organisms, which is reflected in the patterns of the distribution and abundance of the longevous

I gorgonian corals. I Differences in urchin populations among the beds are also important. Urchins were more abundant at the beds surrounding SONGS I than they were at DeI Mar, and behaved differently. The sea urchins in the De1 Mar bed apparently ate drift algae, and in any case there was no I evidence that sea urchin grazing limited the distribution and abundance of kelp (Rosenthal et al L974). In contrast, our cooperative work with

I Tom Dean (KEP) has shown that white urchins may limit the recruiLment of I kelp, and that red urchins have eliminated adult kelp in portions of the San Onofre kelp bed (Dean et al 1984). I Although comparisons among the beds reveal clear and important differences, the same species generally oecur in all of them. Most of I the species regarded as characteristic by Rosenthal et a1 (L974) were I also common in the kelp beds near SONGSand were included in this study. l I I I I I I 13 I I

I FIELDMETHODS: SURVEYSOF BENTHICINVERTEBRATES

I Station Location and Configuration I The studies reported here were done in kelp forests in northern San Diego County, California (Figure 1). Four monitoring stations were t established in FaIl 1980. The site nearest the Units 2 and 3 diffusers was in the upcoast, offshore portion of the San Onofre kelp bed (Figure t 2, SOKU). A second station near the diffusers was located in the downcoast, offshore portion of the San Onofre kelp bed at approximately t the same depth (SOKD). Distant control sites were located in the San I l"lateo kelp bed (Figure 3, SMK), and in the Barn kelp bed (Fieure 4, BK). The location of SOKUwas chosen to be within the area predicted to I be most affected by the operation of Units 2 and 3. Most of the stations were placed in about the same depth of water in what appeared to be I persistent areas of kelp. BK and SMKhrere thought to be far enough away from SONGSso as not to be affected by the discharged cooling water. A11

I stati.ons were located on hard substrates at least 10 meters from the l nearest sand plain. The giant kelp population at the Barn kelp site declined I throughout 1980, and had essentially disappeared by the end of the year. Giant kelp was sti1l not present at our study site in BK at the time of T our last survey. The caL:se of the die-off is not known, but we have speeulated that it was due to increased sedimentation .dur'ing L978- 1980

I (Dixon et al 1988) . t Each station consisted of a surface buoy anchored by a metal plate which marked the origin of four 40-n transects (oriented at 0350 , !25o, I 2L5o, and 3050). The transects were marked with l/4-inch steel I L4 I I

I reinforcing bar stakes. Ten permanent I-m2 quadrats were positioned I every 4 meters along each transect (Fieure 5). A description of the nearshore oceanographic conditions in northern San Diego County and of t the cooling system for the power plant is presented in Dixon et al I (le88). I SamplingFrequencv Surveys were conducted every 2-4 months from November 1980 to ,t April 1983, approximately semiannually from April 1983 to November 1984, and every 2-4 months from November L984 to December 1986. Twenty- I two surveys were done (Table 1). Survey 1 was not used for the analysis because methods were still being developed and field technicians were I stil1 being trained. l Training I Training rlives were made before all but one survey. Training was done at SMK,which was considered the most difficult station due to high I diversity and abundance. Several- quadrats were randomly chosen from the sampling array, and were sampled by each diver. The results were

I used immediately to standardize the surveys. After the training dive, I counts were compared to those of the field leader, sampling techniques discussed, and another set of quadrats was sarnpled. This was repeated t two or three times, in order to insure that all divers were sampling in the same manner. I I t 15 t I

I Sampling The species of animals and plants that were counted are listed in t Table 2. (Note Lhat the bat star, Asterintminiata, is referred to by t its old name, Patiria, in the rest of this report.) Twelve species of snails were added to the list late in the preoperational period. These I were not sampled in the early surveys because of lack of resources. Later when we were able to employ a stable group of field assistants, we I increased the number of species counted. In order to avoid disturbing the sessile species, the quadrats were sampled non-destructivelyi i.e.,

I only those animals on the surface of the substrate were counted. t Animals which could escape out of the quadrat were counted first; those which crawled into the quadrat after the eensus began were not counted.

Giant kelp and other algae were counted, but the methods and results are

reported elsewhere (Schroeter et al 1988a). t The percent cover of selected substrates was estimated by noting the size and type of substrate under 15 uniformly distributed points

I within each quadrat. The categories of substrate were "si1tr" sand, I pebble, cobble, boulder, reef, and bedrock. In addition, the percent covers of live Macrocystis holdfast, dead Macrocystis holdfast, and the T colonial polychaete, Phragmatopoma californica, were estimated. Substrate categories were based on their greatest'diameter. Pebbles I were l-5 em. Cobble was recorded, in three classes (6-10 cm, 11-20 cm, and 21-30 cm), as were boulders' (31-40 cm, 41-50 cm, and >50 cm). The il substrate categories corresponded closely to those of the Wentworth

scale (Tab1e 3).

"Si1t" was not recorded until October 1985, when a fine, cohesive I soft sediment was first noted at our study sites in the San Onofre kelp I I5 t I

I forest. Obviously, a diver in the field could not distinguish accurately between very fine sand and silt. However, most sands found

I within the kelp beds were coarse, and the substrates normally t characterized as silt in the field turned out to have a median phi near 4.0, and a dispersion of about I when analyzed in the laboratory. I Beginni-ng in I985, patches of this fine material were periodically mapped in the field, and samples were collected for laboratory I analysis. Grain size and Total Organic Carbon (TOC) were determined. These fine sediments were nominally characterized as "silt" in the t fie1d, and in the context of our field surveys the term is used in this t report, despite the fact that some of these fine sediments would be characterized as fine sands using the standard Wentworth scale. t I l I t I I I l L7 I I

FIELDMETHODS: KELPRECRUITMENT SURVEYS

I Station Location and Configuration t Eleven to 15 stations were sampled in the San Mateo kelp forest, and 24-44 stations were sampled at San Onofre. Stations were arrayed I more or less uniformly in the San Onofre and San Mateo kelp beds (Figure 5 ) . At San Mateo a smaller array was established which only covered T areas where kelp had been most persistent.

I SamplingFrequencv I Surveys were conducted approximately quarterly beginning in September 1981. However, the duration of the surveys and the time t between them varied considerably and i.rregu1ar1y, depending on sea conditions. Sixteen surveys were completed between FaI1 1981 and Fa11 I 1985 (Table 4).

I Sampling T Two sampling protocols were used during the course of the kelp recruitment study. From 1981 through 1983, giant kelp, sea urchins, and I sea stars were counted in a single 4-*2 quadrat along each of three transects at each station. The quadrats were randomly Placed between 2 I and 10 m along transects marked with a 10-m tape. The transects were laid out on random compass bearings (Figure 7). The quadrats were

I sampled destructively during standard surveysi i.e., boulders and I cobbles were turned over and pebbles carefully searched through, in order not to overlook cryptic organisms. During the October 1981 t,? t survey, a 1-m' quadrat in the corner of the 4-m' guadrat was first I 18 t I t sampled nondestructively in the manner described above for the survey of benthic invertebrates .

I From 1984 through 1986, five 1-*2 quadrats were placed between 10

and 35 m along a single randomly oriented transect (Figure 7). The

I quadrats were placed at random points within 5-m strata and staggered, t with two on one side of the transect and three on the other. Three quadrats were sampled destructively and two non-destructively. During t the June 1986 survey, orr. I-*2 quadrat was sampled in the manner of the t survey of benthic invertebrates, as had been done in 1981. I t I t I t I I I I 19 I J

I DATA BASE MANAGEMENT t Upon completion of a field survey, data sheets were checked, and t errors, ambiguities, or confusing entries were resolved with the help of the sampler who took the data. After being checked, the field data t were transcribed onto keypunch sheets. The keypunch sheets were checked, corrected, and sent to Hiro's Keypunch Service. Keypunch I personnel were asked to verify all data by punching it twice and checking the second entry against the first.

I A magnetic tape was received from the keypunch facility, and the I data were downloaded by TITAN. A printout of the entire data set (by survey) was made, and stratified random pages were chosen to check for t keypunch and transcription errors. Ten percent of the data was checked Iine by line. If no errors were found, checking ceased. If one ormore I errors were discovered (either keypunch or transcription errors), another 10% of the pages was checked. This procedure continued until no

I errors were discovered. A11 lines of small data files wete checked. t After checking for keypunch and transcription errors, a Statistical Analysis System (SAS) program was run on all data sets to I check for duplicate lines, and these data were eliminated if oresent. The SAS programs .used to check for errors are included in the history I secticn of each data base. F:.nal1y, the establishment software described in the MRCData Standards Document checked for outlying or t impossible values. If no errors were detected, the data base was I established as an official MRCdata base. After data bases were established, personnel of the Marine Review t Committee, Inc. randomly selected 10 percent or 300 records, whichever I T I t was less. These were checked against the raw data. We then resolved all discrepancies and identified errors. The error rate for our data bases T is less than one percent. t The SAS programs used to construct data bases which were used in this report and the programs for the analyses and construction of the T Tables and Figures are shown in Appendix B. The actual code is contained in files on our project software disk and is available to all J who have access to the MRCcomputer system. t r

I t I t I T T

J I I

I ANALYSIS

I This study was designed with the Before-After/Control-Impact- I Pairs (BACIP) analysis in mind. The basic design and the development of the analytic framework are presented by Stewart-Oaten (f985) and t Stewart-Oaten et aI (1986). This experimental design requires that replicate surveys be conducted during roughly equal intervals before J and after the environmental perturbation of interest, which in the present case is the commencementof the normal, sustained operation of

I SONGSUnits 2 and 3. From the spring of 1980 through the spring of 1983, I the pumps for one or both of the new generating units were being tested, but no power was generated until FaII 1982 (Figures 8 and 9). Since May

1983, Units 2 and 3 have been operating at the level that is expected to

be normal. For the benthic survey, the period from October 1980 through T April 1983 is considered "preoperational. " Since the species we were monitoring tend to be long-lived and to recruit sporadically, w€

I thought there should be a time lag between the start of normal plant I operation and the beginning of our operational surveys. We have designated surveys made after October 1984 as "operational." The I period from April 1983 to October 1984 r,ras designated the "interim" period, sampling frequency was halved, and data collected during the t two surveys in this period were not used in the BACIP analysis. In order to obtain an accurate estimate of the mean at each survey,

I replicate spatial samples were taken at each impact and control I location at about the same time. For each sun/ey the difference, or delta, between the mean abundance estimates at the impact and control I. sites was calculated. For the jth survey: t 22 I I

D.- = Y..-j - Y.^j I i inpact control

I, Under the null hypothesis, one would expect that the average delta in I the operational period would not differ significantly from that in the preoperational period. We tested the nu11 hypothesis with a t-test and I a Wilcoxon rank sum test (Snedecor and Cochran L967). The alternative hypothesis was simply that the "Before" and "After" deltas differed t since we had no a priori expectations concerning the sign of any plant effects. Therefore. two-tailed tests were used in all the analyses. t The t-test is based on the following assumptions regarding the I deltas: l) Effects are additive;2) The samples in the before period are drawn from the same population and have a common mean; 3 ) I Observations are independent; 4) Observations are drawn from the same distributioni 5) Observations are normally distributed; and 6) I Variances in the two treatments are equal. For equal or nearly equal sample sizes, violations of the last three assumptions have little

I effecr on the t-test (Class et al L972; Stewart-Oaten 1986), and will I not be discussed here. The first three assumptions, on the other hand, are very important. T The preoperational data were tested for additivity using Tukey's test and, where necessary, log transformations were used to produce I additivity. In the cas.: of density esti.mates, the sPatial- replicates were averaged at each location and then transformed, using logarithms

T of the form Y = loBr'(x + c) after cases of zeros at both impact and I control were deleted. Estimates of percent cover were first transformed using the angular transformation (Snedecor and Cochran I L967) in order to normalize the data, and then subjeeted to a log T 23 I I

I transformation, if necessary, to produce additivity. Adequate transformations were found for most species. A constant, c, was added

I before taking logs if the mean density was occasionally zero at one of I the stations. Two constants were used, 1 and I/n, wheren is thenumber of quadrats sampled. t After testing for additivity, we examined the preoperational data for temporal trends by plotting the deltas against time and by doing T regression analyses. If there vrere no significant trends, we assumed that all the preoperational deltas were from the same statistical

I population. I Positive serial correlations in the data result in underestimates of the true error variance of the deltas, and hence wrongly increase the I chance of finding a statistically significant BACIP result. We tested for serial correlations with the Von Neuman test, and in most cases t found no significant serial correlations. However, it must be noted that because of small sample size (n <10), the power to detect such

I correlations is generally smal1. One solution to the problem of serial I corelations is to conduct an analysis which explicitly estimates the autocorrelated errors. We elected not to do this, again because of t small sample size, and instead performed the standard BACIP analysis, wj.th a ca.utionary note in cases with significant results. I . Ser.eral screens were written i:.to the computer programs used irr the stalistical analysis. First, we selected those species which were

I present and counted at both the impact and control sites during at least I two preoperational surveys and which had a mean abundance at one of the stations in the San Onofre kelp forest of at least 1 / l0-m2 on at least I one occasion during the six years of observations (Tab1e 5). That is I 24 I I

I equivalent to four animals at one of the stations on a survey. The species that passed these scrirens were then subjected to tests of the I assumptions underlying the BACIP analysis. Only those species for which P >= 0.10 for additivity, P > 0.05 forserial correlation, andP > t 0.05 for linear trends in the preoperational period were analyzed for I Before-After differences in the deltas. Frequently, more than ond transformation of the data passed the tests we imposed. This would not t be cause for comment were it not for the fact thar different transformations often produce different results of the t-test. In I order to objectively select a transformation, w€ passed the data t through one more computer screen. We selected the transformation that returned the largest P-value for additivity, unless Padd > 0.50 for more I than one transformation. In that event, we chose the transformation which h"d Padd > 0.50 and the largest P-value for a linear trend. The I unscreened results of the tests of assumptions are presented in I Appendix A. Effects of Perturbations Unrelated to SONGS

I Toward the end of the study, a front of grazing red and purple sea I urchins began moving across the control station at SMK. By the last survey about half the quadrats had been gtazed. In order to test t whether any of the species had been affected by the activities of the urchins in the front, w€. compared, quadrats that had .been grazed with t those that had not. Dividing the quadrats into these two categories was a straightforward procedure, because we could easily tell where the

I front had been and were able to observe its movement. After dividing I the data into affected and unaffected quadrats, we made temPoral plots

I 25 I I

I of abundance by category to see if there were obvious differences. We also assigned surveys to a "Before" or "After" period, depending on when

I they were conducted relative to the appearance of the urchin front. t Then with the unaffected quadrats as "Control" and the affected quadrats as "Impact," we did a BACIP analysis. I The arrival of the urchin front at the control site is obvious by the sudden increase in the density of red and purple sea urchins (Figure t 10A and B). In the present context, changes caused by the urchin front are only of interest if they affect the utility of the control. The

I following species may have been affected (table 6; Figures 11-13): I Astraea undosa, Cypraea spadicea, Nassarius spp., Crassispira semiinflata, Patiria miniata, and Styela montereyensis. Rather than I make a judgment for each species as to whether it was affected by urchins (or silt - see below), we ran the analyses twice, once using I means calculated from all quadrats and once with means calculated from unaffected quadrats.

I During the course of our study there occurred two other events I which were also clearly unrelated to the operation of SONGSbut which couid cause period by location interactions in the abundance of some t echinoderm species. In 1981, and especially in 1983 and L984, a series of 'ep.'i.zootics similar to the episode observed in Baja, California I (Dungan et a1 1982), virtually eliminated shallow water sea star populations in the southern California Bight (Tegner and Dayton 1987).

I Since initial densities were much lower at the control site in SMK, the I absolute change was also lower there. A second perturbation which was unrelated to SONGSwas the commercial harvesting of red sea urchins. t Red urchins were initially more abundant at the control site in the San I 26 I I

I Mateo kelp forest than in the San Onofre kelp forest. Harvesting was heaviest during the interim period. By late L984, fishermen could no

I longer find sufficiently dense populations in SOK to make harvesting I economically feasible. However, dense populations were still found at SMK, although the roe were of poor quality. We have not included sea I stars or red urchins in our analysis because of these severe perturbations. The other species we counted were subjected to the I computer screens described above and then analyzed using the BACIP I approach. t Evidence of an Effect of the Power Plant The BACIP analysis identifies significant operating period by I location interactions. It is a test of whether the average difference in the abundance of organisms at the control and impact sites changed I after Units 2 and 3 began operating. The BACIP analysis is not a direct test of whether SONGSaffected the biota, although that may well be a

I reasonable inference in the case of a statistically significant result. I Such an inference is greatly strengthened if there are plausible mechanisms by which SONGScould produce the observed changes, and I weakened by the existence of probable extraneous causes. During the operational period there was a marked increase in silts t and fine sands at,the impact site and surrounding areas. Because changes in substrate could reasonably be expected to' affect the

T abundance of benthic animals, the origin of the sediment and the cause I of its deposition in the kelp forest immediately became topics of inquiry. On the one hand, it is of interest as a possibly confounding I variable. On the other hand, it is of concern because it may be a result t of the operation of SONGS. 27 t I

I In the context of our monitoring studies, there is no thoroughly satisfactory way of dealing with the problem, because there is no way to

I completely isolate the effects of sediments from possible effects of I SONGSwhich are not directly related to sediments. Our solution to the problem was to test for operating period by location interactions I twice - once using all the data, and once using only data from quadrats that appeared to be unaffected by the influx of fine sediments. In I addition, we directly tested for effects of the sediments at the impact site by comparing affected and unaffected quadrats, This has the

I advantage of controlling for unrelated SONGSeffects because the I guadrats are close to one another (a11 within an 80-m x 80-m area). 0n the other hand, the determination of which quadrats were affected by I silt at SOKUis not clearcut, because the position of the silt changed somewhat from survey to survey. We defined affected quadrats as those I which had at least 25 percent cover of silt on any survey. Twenty-five percent was chosen as the cutoff, because it was our impression that

I when there was less cover, the sediment was generally a thin layer and I less stable. If this impression is accurate, the analysis is testing for the effects of relatively persistent silt deposits, but not I necessarily for the effects of brief influxes of thin layers of siIt.

I Generalitv of the PopulationEstimates In order to see how representative of the impact and control areas

I our monitoring stations were, we compared the estimates of density at I the benthic monitoring stations with the estimates from the surrounding t I 28 I I t kelp recruitment stations using t-tests. The number of recruitment stations in each area varied as follows:

I 1981 1985

SOKU 9 o I SOKD 6 6 SMK 8 5 I t I I I I I t I I I I I I 29 I I

I RESULTS

I Effect of Silt Accumulation t The influxof silt at SOKU is apparent in Figure 14. The quadrats that accumulated silt must have differed from the others in depth or I bottom topography, because the cover of sand was almost always l0 or 15 percent higher before the appearance of the finer sediment (Figure I r4B). None of the species we monitored showed significant increases

I where silt accumulated. This is not surprising, since nearly all of I them are usually found associated with hard substrates. 0n the other hand, the density of several species declined where silt was abundant I (Table 7). In the case of the predatory snails, Kelletia kelletii (Figure 15A), Maxwellia gemma(Figure 168), and the sea star, Patiria I miniata (Figure l5A), the deeline in the affected quadrats seems to be an effect of the added silt. The snail, Flurexiella s.antarosana (Figure

I l5B), and the sponge, Tethya aurantia (Figure l7A), also declined inthe I affected quadrats relative to controls, and the BACIP tests were significant. However, the results are somewhat less convincing because I both species declined in the control quadrats. One other species appears to have been adversely affected by the accumulation of silt at I SOKU. The white sea urchin, Lytechinus anamesus, declined sharply in density where silt was abundant (Figure 178). BACIP tests could not be

I done because changes prior to the appearance of the silt were not I additive. It seems obvious that accumulations of fine sediments are I deleterious to animals that prefer hard substrates, as do most of the t 30 I I

I species we monitored. Periodic influxes of sand are normal events in kelp beds and may contribute to community stability by clearing space.

I However, a per:sistent increase in the percent cover of sand and silt t would undoubtedly change community composition. In order to evaluate the significance of the changes we observed at SOKU, one needs to know I if the increase in silt is a natural event or if it is a funcEion of the operation of SONGSUnits 2 and 3. t There have been several studies designed to determine the distribution and characteristies of the cohesive soft sediments that

I appeared at SOK. During the course of our monitoring studies of benthic I invertebrates and kelp recruits, the percent cover of silt was estimated. In addition, in October L985 and again in July-August L987, t we collected sediments for laboratory analysis at about 60 sites in a uniform grid that included the San Onofre kelp forest. Finally,. in I December 1986 and in September-October 1987, we estimated the percent cover of silt in l-m2 quadrats, and the cover of algae and sessile

I invertebrates on random boulders at about 25 sites located along two I transects perpendicular to the diffuser lines. In the laboratory, sediments were subjected to grain size I analysis, and total organic carbon was determined. A subset of the sediment samples and samples from the lay-down pad at the SONGS I construction site were analyzed for mineral content. The Iay-dotn pad was released between late Deeember L984 and early January 1985, and it t is possible that it was the source of some of the fine materials later I observed in the kelp forest. The results of these various studies are stiLl being analyzed and I will be reported under separate cover (Schroeter 1988). However, we will give a brief preview here: I 31 t I t I. A thick deposit of cohesive, fine sediments appeared at the upcoast impact site in 1985, and was stil1 present in July I 1987. 2. These sediments were generally more abundant near the

I diffusers than farther away (Figures 18-20), and thick I deposits were observed in the upcoast part of the kelp forest. I 3. This cohesive sediment was finer and higher in total organic carbon than the other soft sediments in the kelp forest. I 4. The percent cover of algae on boulders was lower near the diffusers than farther downcoast, and was significantly

I negatively correlated with the percent cover of the cohesive I sediment. t Operating Period by Location Interactions During the course of our study of benthic invertebrates, w€ I monitored the abundance o species. 0f these, 19 passed the various staEistical screens, and the data for these species were subjected to

I the BACIP test for an operating period by location interaction. t Gastropod Mollusks I ?he pattern that is most apparent and convincing is a general decline in the abundance of gastropod mo-1"lusksat the impact site in the I uPcoast portion of the San Onofre kelp forest relative to the distant I control sites (Tables 8 and 9; Figures 24-69). I

I 32 I I

I CatliostomasPp. These trochid gastropods (Figures 2L-24) are omnivores that are

I often found on giant kelp and other algae in kelp forests. The animals I included in this category are mostly Calliostorna supragranosum, but also some _9. gloriosum and an occasional g. annulatum. Timothy I Herrlinger (personal communication) estimated that about 75% of these snails were C. supragranosum. Calliostoma was only sampled twice I during the preoperational period. Initially, it was most abundant at the impact site, but declined throughout the interim period, whereas

I populations at the control sites increased somewhat (Figures 21 and I 23). The patterns were essentially the same whether all the data vras used or only data from quadrats unaffected by silt or urchins. The I changes in density resulted in significant differences in the deltas 24). t for the two operating periods (Tables 8 and 9; Figures 22 and Tegula aureotincta

I The pattern for Tegula aureotincta is similar to that of I Calliostoma in that initial densities were highest at the impact site and close to zero elsewhere (Figures 25 and 27). The patterns were I similar for both types of quadrats; At the impact site the density declined and remained 1ow, whereas the control populations showed I modest increases. This resulted in decl'r-nes in the deltas (Figures 26 and28), but thedifference in the "before" and "after" deltas was only

I significant for the SMKcomparison (Tables 8 and 9). I I

I 33 t I

I CVpraeaspadicea Cypraea spadicea occurred in 1ow numbers at all four monitoring I stations throughout the preoperational period (Figures 29 and 3l). In the operational period there was a marked increase in the San Mateo kelp

I forest, but not elsewhere. In fact, there was a decrease at Barn kelp I where densities had been highest. These changes are reflected in significant changes in the deltas for comparisons between the impact I stationand one (Table 8; Figure 30) orboth (Table 9; Figure 32) of the distant controls. There vras no significant change in the deltas when I the two SOK stations were compared. The lack of recruitment at SOK relative to SMKis suggestive, but one hesitates to ascribe the cause to

I SONGSwithout additional evidence, since there was a marked decline and I 1itt1e subsequent recruitment at BK.

T Conus californicus Conus californllgs (Figures 33-36) is a predatory snail that is I often associated with kelp holdfasts, perhaps because that is the home of their prey. These commonsnails were most abundant at the stations

I in the San Onofre kelp forest during the operational period, and within T SOK, more abundant at SOKU(Figures 33 a:rd 35). During the operatj-onal period, populations in SOK declined relative to those in SMKand BK. I There apparently was recruitment at both distant control sites, but not at San Onofre. Within SOK, the upcoast population declined relative to I the downcoast population. Although there was a strong seasonal component to the changes in

I population densities, this was generally evident at all the stations. I The relatively larger decline at the impact site during the operational

I 34 T t

I period resulted in smaller deltas for all comparisons (Figures 34 and I 36). The differences in the average "before" and "after" deltas were significant in each case (Tables 8 and 9). The patterns were I essentially the same regardless of the presence of large quantities of si1t. I Crassispirasemiinflata

I Crassispira semiinflata, occurred at relatively low densities at I all the stations, although it was most abundant in SOK. During the course of our observations the population densities have varied widely t and asynchronously. The population at the impact station declined sharply during the early interim period and then fluctuated about a I lower mean density. At the control sites, abundances stayed about the same or increased. These changes resulted in smaller average deltas

I during the operational period (Figures 38 and 40). The differences were I significant for all the comparisons using data from quadrats that were unaffected by silt or urchins, and significant for the BK comparison I using all the data (Tables 8 and 9). t Kelletiakelletii Kelletia kelletii is a large predator and scavenger that is a

I conspicuous member o.f the fauna in most kelp forests. These snails were I abundant at all the monitoring sites during the preoperati.onal pericC, but generally were more numerous at San Onofre than elsewhere (Figures I 41 and 43). Throughout the interim period, densities declined in both areas of the San Onofre kelp bed relative to the distant control sites. I This resulted in smaller average deltas during the operational period t 35 I I

I (Figures 42 and 44). The difference in the average deltas in the two operating periods was slight and not significant for the comparison of I the two stations in SOK (Tables 8 and 9). The difference was statistically significant for the SMK comparisons and for the BK t comparison for data from all quadrats (Tab1es 8 and 9). A striking I pattern is the sudden and ephemeral decline in abundance estimates in late L982. We suspect that the snails were ptesent but cryptic. One I conjecture is that they buried themselves in response to large swells.

I Maxwellia gemma

In the preoperational period, Maxwellia genma was counted twice.

I At that time it was present at low densities at the control stations but T quite abundant at the impact site (Figures 45 and 47). It declined at the impact site during the interim period and remained at low densities, I whereas the average abundances at the control stations increased. The pattern was essentially the same for both groups of quadrats. These I shifts in density resulted in lower average deltas during the

operational period (Figures 46 and 48 ) . The operating period by I location interaetion was significant for all comparisons (Tables 8 and t e). t Mitra idae Mitra idae is'a relatively abundant snail that was generally more I numerous in SOKthan at the control sites. Within SOKits density was highest in the upcoast portion of the bed. During the operational

I period, the mean density of Mitra increased at all the monitoring I stations except the impact station in upcoast SOK, where it declined

I 35 I I t slightly (Figures 49 and 51). The changes in the relative abundance at the impact site resulted in lower average deltas during the operational

I period (Figures 50 and 52). The differences were not significant when I data from all quadrats were used. However, there was a negative trend in the deltas during the operational period for the SMK and BK I comparisons which was significant for the latter (Table 8 ) . When data from quadrats unaffected by urchins or silts were analyzed, the BACIP I results were significant for both the SOKDand BK comparisons.

I Murexiellasantarosana I The pattern for Murexiella santarosana is generally the same as for Maxwellia gemma. The densities at the SOK stations declined during I the interim period and remained low, whereas the abundances of these snails increased at the distant control sites (Figures 53 and 55). As a I result, the average deltas are smaller during the operational period (Figures 54 and 56). However, the results of the BACIP analysis are

I short of statistical significance for all but the SOKDcomparisons for I data from all quadrats (Tables 8 and 9 ) . I Nassarius spp. Nassarius were generally more abundant at the stations in SOKthan t elsewhere until the last few surveys (Figures 57 and 59). The 1'aglerns in the deltas are roughly similar to those of the other species of

I snails (Figures 58 and 60), but the differences in the "before" and t "after" deltas are not significant for any of the comparisons (Tables 8 and 9). I I 37 t I

I Ophiodermellainermis

Like Nassarius, Ophiodermella inermis were only counted twice t during the preoperational period. These snails were uncommon, and I there was little difference in density in the preoperational and operational periods (Figures 61 and 63). There were no significant I differences in the average deltas of the two operating periods (Tables 8 I and 9; Figures 62 and 64). I Pteropurpura festiva Pteropurpura festiva were counted twice during the preoperational I period. During that time they occurred at relatively low numbers at the distant control sites but were quite abundant in the San Onofre kelp I forest (Figures 65 and 67). They declined at both SOK stati.ons during the interim period. The average density of populations at SMK and BK

I increased during the "after" period. The patterrr was the same for data I from both types of quadrats. These changes in density resulted in smaller deltas during the operational period for comparisons with both I distant controls (Figures 65 and 68 ) which were all statistically significant (Tables 8 and 9). There was no significant change in the l SOKU-SOKDdeltas.

I Sessile I nvertebrates I The changes in the density of the other species of invertebrates that could be analyzed did not fit a single pattern. Although there are I some suggestions of an effect of SONGS,the evidence is less compelling than for the snails. I I 38 T I

t Tethva aurantia The density of Tethya was always low, patticularly in the

I downcoast portion of SOKand at San Mateo (Figure 59 and 71). Densities I at the upcoast station in the San Onofre kelp bed and in Barn kelp forest were higher, but declined during the interim period. There was no I consistent pattern in the deltas (Figures 70 and 72), and none of the differences in the "before" and "after" deltas were significant (Tab1e I 10 and 11).

I Muriceacalifornica I During the preoperational period, M. californica was rare in the San Onofre kelp forest and abundant at the control sites (Figures 73 and I 75). There was substantial recruitment at all the stations, but less at the impact site than at the downcoast station in SOK. On the other hand, I the proportional increase was greater at the impact site than the distant controls, which resulted in significant BACIP tests (Tables 8

I and 9; Figures 74 and76). To add complexity, the proportional decrease I in density during the operational period was also greater at the impact site, which res.ulted in significant negative trends in the deltas I (Tables 8 and 9; Figures 74 and75). In the absence of a demonstrated mechanism, tre do not think the observed density changes should be I interpreted,ras ef f ects of SONGS.

I Muricea fruticosa I Like its congener, Muricea fruticosa was rare in the San Onofre kelp forest during the preoperational period (Figures 77 arrd 79). There I was some recruitment in 1984. but less than for M. californica. The I 39 I I

I density of M. fruticosa was stil1 very low in the operational period, but higher in the downcoast than upcoast portion of the San Onofre kelp

I forest. This resulted in a significant difference in the average deltas I for the two operational periods (Tab1e 10; Figure 78 ). A decline in density at SMKresulted in a significant difference in the deltas in the I other direction (Table 10; Figure 78). There is no evidence of an effect of SONGS. t Strongvlocentrotus p urpuratus I Purple sea urchins have always been more abundant at San Mateo than elsewhere (Figures 79 and 81). This may be related to habitat

I availability. Like Cypraea, purple urchins are generally found in the T cryptic habitats that are in greater supply at SMKthan at the other sites. At SanMateo there was a general decline in S. purpuratus during I the preoperational period, and a general increase during the operational period. Within SOK, purple urchins were more abundant I upcoast than downcoast during the preoperational period, but were I slightly less abundant at the impact site during the operational period. This resulted in a significant difference in the average deltas

I for the two operating periods (Tables 10 and 11; Figures 80 and 82).

There was also a significant BACIP result for the SMK comparison for I data from quadrats which were not affected by silt or urchin fronts T (Tab1e 11; Figure 82). Hovrever, this result reflects events at SMK, particularly a large increase during the operational period. This may f indicate that recruitrnent was inhibited at SOK or that SOKwas a poor habitat for purple urchins, since they were always uncommonthere.

f

40 I I

I Lvtechinus anamesus

During the preoperational period, Lytechinus anamesus was more

I commonin the San Onofre kelp forest than at the control sites (Figures I 83 and 85). Since 1983 there has been an increase in the density of white urchins at many sites in the California Bight (Tegner and Dayton I 1987). In some places, as at the San Onofre and San Mateo kelp forests, this resulted in high densities of these urchins inside kelp beds. In t the past they have been most conmon outside the kelp beds and in deeper I water. We think the change may be related to the decline of predatory starfish due to disease. At our study sites the increases have been I greater at San Onofre than at the control sites. Later in 1986' however, there was a rapid increase at the station at SanMateo. 0n t average, densities increased at SOKUrelative to distant controls, but increased at SOKDrelative to SOKU. Although many of the changes in the

I deltas are statistically significant (Tables 10 and 11; Figures 84 and t 86 ) , because of the latter trend and the possible confounding effect of changes in sea star predation, we think it is unlikely that the observed t changes are a result of the operation of SONGS. t $yglg monterevensis This solitary tunicate was very abundant in the downcoast portion

I of SCI{.during the preoperational period, and was common elsewh.ere t (Figures 87-90). It declined to near zero everywhere before Units 2 and 3 went on line. During the operational period there was a I proportionately greater increase in density at BK than at the impact site. This resulted in significant BACIP t-tests for this comparison t (Tables I0 and 11; Figures 88 and 90). Both stations in SOKbehaved l 4L I t

I similarly, and the difference inthe average deltas for the "before" and "after" periods was not significant. The results are suggestive of a I negative effect of SONGSon recruitment. t l I t t I I I t t I I t t l 42 I I

I DISCUSSIONAND CONCLUSIONS

I The results of this study demonstrate that there was a general T decline in the abundance of many species of invertebrates in the San Onofre kelp forest after Units 2 and 3 of the San Onofre Nuclear I Generating Station began operating. The evidence strongly suggests that the changes in the biota were caused by the operation of the new t generating units and were not sinply correlates. The results of the BACIP analyses were generally highly significant and, for several

I species, the decrease in abundance was more severe at the station in SOK t that was closest to the diffusers. Most of the species affected were gastropod mollusks and can be t divided into two groups: species for which there were few samples in the preoperational period, and species for which there were many samples.

I Although the temporal patterns of abundance were similar for snails in

both groups, the inference of a power plant effect is much stronger for

I the latter. In addition to the snails, the purple sea urchin, I Strongylocentrotus purpuratus, seems to have been adversely affected by SONGS. The evidence is weaker, since it is based on much better t recruitment at a control site, where abundances of this species have always been higher, than at the impact site. Similarly, the solitary I tunicate, Styela m.ontereyensis, recruited bettef 3t :r control site tharr at the impact site during the operational period. The presumption of an

I effect of the power plant is stronger for this species, because it had t been abundant in SOK during some earlier surveys. Although we do not have the information necessary to identify the t mechanism underlying the statistical evidence of a power plant effect, I 43 I I t a likely cause is an increase in fine sedimentss in the San Onofre kelp forest. Two of the species for which there was statistical evidence of

I an effect of SONGS, Kelleti4 kelletii and Maxwellia gemma, also I appeared to be adversely affected by a build-up of a cohesive, fine sediment at the impact site. However, the appearance of deep deposits t of this material is not a sufficient cause for the observed population declines, because the numbers of most species began to decrease before T large deposits were noted. A related phenomenon that may have negative effects is the increase in the flux of fine materials at SOK caused by an t interaction between the diffusers and natural sources of sediments. I Inman (1987) proposed a similar interaction between the diffusers and the materials released from the lay-down pad in 1984 and 1985. It is t possible that the diffusers interacted in a similar way with the large amount of fine material introduced to nearshore waters from streams t during the winter storms of 1983 (Reitzel et a1 1987 ) to increase the flux of fine material at SOK.

I A frequent dusting of fine sediments on hard substrates in the San t Onofre kelp forest could interfere with 1arva1 settlement and might decrease the chances of the successful attachment and development of I eggs. A11 the gastropods we have discussed attach gelatinous egg masses or egg capsules to hard substrates or algae. After several days or I weeks, the veliger larvae are rele;'-sed. The length of time before settlement is not krr=ownfor these species. However, in general , the t free veliger stage lasts from a few hours or days to two to four weeks t (Hyman L967). If the larva1 life is less than a day or so, a negative effect on egg laying or development could result in a decrease in 1ocaI I adult population densities . l 44 I t t Finally, one might reasonably ask, how general are the results? Are the monitoring stations representative of the surrounding area? I The comparison of the density estimates made at the benthic monitoring stations with those made at the surrounding kelp recruitment stations

I indicates that there are few differences among sites (Tables l2-L4). T However, one set of comparisons demands special comment. In 1981, Conus californica was more abundant at the benthic stations than at the kelp I recruitment stations at San Onofre. In 1986, the pattern was reversed. There were no differences in the San Mateo kelp bed. Since these

I estimates really constitute a simple, unreplicated (in time) sample in I the "Before" period and one in the "After" in the BACIP context, one ought not treat them as, representative. We simply may be unduly I impressed with sampling error. Nonetheless, we find it difficult not to wonder at the differences, especially since they are so similar in the t two parts of SOK. The only colnmon element that we can think of is the change in the density of ke1p. In 1981, both benthic survey stations t were in areas of abundant kelp, whereas in 1986 there was no kelp at t either station. There was still kelp at many of the kelp recruitment stations, however. It is possible that differences in the abundance of I Conus may be"a function of kelp density, and that this may also be one of the mechanisms underlying the BACIP results. I I I

I 45 l I

I ACKNOWLEDGMENTS I Jon Kastendiek was a principal investigator on this project for t several years. He helped design the study and provided much of the early direction. Several people who are not on the permanent staff of I the Kelp Forest Invertebrate Ecology Project have contributed significantly to our research. These include Bob Brantley, Dennis

t Jung, John Levin, Roy Pettus, Gene Pillard, Adam Ravetch, and David t Young, who assisted in the field. Shayne Berridge, Julie Mattison, Leslie Meade, and Nikki Miguelez provided help in the laboratory, and I did an excellent job at the demanding and often tedious task of data base preparation. Jan Callahan and Keith Parker provided statistical T advice. Jan Callahan and Art Carpenter developed the software to I perform the BACIP analysis and tests of the assumptions of the t-test. T I I I I I t t 46 J I

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Clarke, W.D. and M. Neushul. L967. Subtidal ecology of the southern T California coast. In: T.A. Olson and F.J. Burgess, eds. Pollution and Marine Ecology. John Wiley & Sons, New York. I pp. 29-42. .' Day, R.W. and R.W. Osman. 1981. Predation by Patiria miniata I (Asteroidea) on bryozoans: prey diversity may depend on the r mechanism of succession. Oecologia 51:300-309.

I Dean, T.A., L. Deysher, K. Thies, S. Lagos, F. Jacobsen, and L. Bost. 1983. The effects of the San Onofre Nuclear Generating Station (SONCS) on the giant kelp, Macrocystis pyrifera: final pre-operational monitoring report for the contract period T May 1981 through October 1982. Report to the Marine Review Committee. Inc. dated March 1983. I Dean, T.A., S.C. Schroeter, and J.D. Dixon. 1984. Effects of grazing by two species of sea urchins (Strongylocentrotus franciscanus and Lytechinus anamesus) on recruitment and surrzival of two species of l kelp (Macrocystis pyrifera and Pterygophora californica). t Mar. Bio1. 78:301-313. Dixon, J.D. and S.C. Schroeter. 1985. Effects of the white sea urehin, Lytechinus anamesus, on populations of giant kelp, Macrocystis pyrifera. Report tr.r the Ma:-in.e Revj-ew I Committee, Inc. dated AprLL 22, 1985.

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't] 47 J I

T Fotheringham, N. L97L. Life history patterns of the littoral gastropods Shaskyus festivus (Hinds ) and Ocenebra poulsoni I Carpenter (Prosobranchia: Muricidae). Ecology 52:742-757. Fotheringham, N. L974. Trophic complexity in a littoral boulder- I fie1d. Limnol. and Oceanogr. 19(1):84-91. Fukuyama, A. and J. Nybakken. 1983. Specialized feeding in mitrid gastropods: Evidence from a temperate species, Mitra idae. I Melvi11. Veliger 26(Z) :96-100.

I Gerard, V.A. 1976. Some aspects of material dynamics and energy flow in a kelp forest in Monterey Bay, California. Ph.D. t diss. Univ. of Ca1if., Santa Cruz. 173 pp. Glass, G.V. , P.D. Peckham, and J.R. Sanders . L972. Consequences of failure to meet assumptions underlying the fixed effects I analyses of variance and covariance. Rev. Educ. Res. 42:237-288

I Grigg, R.W. L970. Ecology and population dynamics of the gorgonians, Muricea californica and Muricea fruticosa. Ph.D. diss. Univ. I oF calir . , san oiego . zET p* I Grigg, R.W. L972. Orientation and growth form of sea fans Limnol. and Oceanogr. L72185-192. I

Grigg, R.W. L974. Growth rings: annual periodicity in two I gorgonian corals. Ecology 55:876-881.

Grigg, R.W. L975. Age structure of a longevous coral: a relative I index of habitat suitability and stability. An. Natur. LO9:647-657 I . Grigg, R.W. L977. Population dynamics of two gorgonian corals. t Ecology 58:278-290. Harrold, C. and D.C. Reed. 1985. Food availability, sea urchin grazing, and kelp forest community structure. Ecology 66: I 1150- 1169.

Hyman, C.H. L967. The fnvertebrates. VoI. VI. Mollusca I. I McGraw-Hil1, New York. 792 pp. I 48 I I

Inman, D. 1987. A working hypothesis for the deposition of cohesive t sediments offshore of the San Onofre Nuclear Generating Station (SONGS). Report submitted to the Marine Review I Committee. Inc. Irvine, G.V. L973. The effect of selective feeding by two species I of sea urchins. Amer. Zoo!. 13:1315. (cited in Lawrence L975)

Lees, D.C. L970. The relationship betr+een movement and available I food in the sea urchins Strongylocentrotus franciseanus and Strongylocentrotus purpuratus. M.S. thesis, Univ. of Ca1if., I San Diego. LL7 pp. Leighton, D.L. 1960. Study of kelp-grazing organisms. In: Kelp investigations quarterly progress report. Univ. of I Ca1if. Inst. Marine Resources, IMR Ref. 60-6, pp. 12-15.

Leighton, D.L. 1968. selection and I A comparative study of food nutrition in the abalone Haliotis rufescens Swanson. and the sea urchin Strongylocentrotus purpufatuE-lstimpson). Ph.D. I diss. Univ. of Calif., San Diego. 197 pp. Leighton, D.L. L97L. Grazing activities of benthic invertebrates in southern California kelp beds. In: W.J. North, ed. The I biology of giant kelp beds (Macrocystis) in California. I Nova Hedwigia 32:42L-453. Leighton, D.L., L.G. Jones, and W.J. North. 1966, Ecological relationships between giant kelp and sea urchins in southern California. In: E.G. Young and J.M. Mclaughlin, eds. Proc. I of the Fif.th rnt. Seaweed Sy*p. PergammonPress, Oxford. pp. I 141-153. Mattison, J.E., J.D. Trent, A.L. Shanks, T.B. Akin, and J.S. Pearse. I L977. Movement and feeding activity of red sea urchins I (Strongylocentrotus franciscanus) adjacent to a kelp forest. Mar. Bio1.39:25-30.

I Mclean, J.H. L978. Marine shells of Southern Californi.a. Natural History Museum of Los Angeles County. Science Series 24, I Revised Edition. 104 pp. Morrj-s, R.H. , D.P. Abbott , and E. C. Haderlie. 1980. Intertidal invertebrates of California. Stanford Univ. Press. I Stanford. 690 pp.

I 49 I I

I North, W.J. L974. A review of the studies supporting sea urchin control as a means of restoring kelp beds. In: KeIp Habitat t Improvement Proj. Ann. Rep. 1973-L974. North, W.J. and J.S. Pearse. L970. Sea urchin population I explosion in southern California coastal wat"rs. S,cience f 167:209.

Osman, R.W., R.t^I. Day, J.A. Haugsness, J. Deacon, and C. Mann. I 1981. The effects of the San Onofre Nuclear Generating Station on sessile invertebrate communities inhabiting hard substrata (including experimental panels). Final I report of the Hard Benthos Project, Marine Science Institute, Univ. of Calif., Santa Barbara. Report submitted I to the Marine Review Committee, Inc. dated May 1981. Pearse, J.S. and A.H. Hines. L979. Expansion of a central California I kelp forest following the mass moriality of sea urchins. I Mar. Biol.51:83-91.

Perron, F. Lg75. Carnivorous Callioglgrg (Prosobranchia:Trochidae) rI from the northeastern PaciEiE. Veliger 18:52-54.

I Reitzel, J., H. Elwany, M.R. Erdman, and K. Zabloudil. L987. SONGSphysical and chemical oceanography. Final report, Volume l1-2. Report submitted to the Marine Review Committee, I Inc.

I Rosenthal, R.J. 1970. Observations on the reproductive biology of I the Kellet's whelk, Kelletia kelletii (Gastropoda : Neptuneidae) Veliger 12(3) : 319-32T-

I Rosenthal, R.J. L97L. Trophic interaction between the sea star t Pisaster giganteus and the gastropod Kelletia kelletii. Rosenthal, R.J. and J.R. Chess. L972. A predator-prey relationship between the leather star, Dermasterias imbricata, I and the purple urchin, Strongylocentrotus purpuratus. I Fish. Bu11. 722670-584. Rosenthal, R.J. , t^t.D. Clarke, and P.K. Dayton. I974. Ecology and natural history of a stand of giant kelp, Macrocystis pyrifera, I off Del Mar, California. Fish. Bu11. 72:670-684. I 50 I I

Schmitt, R.J. 1982. Consequences of dissimilar defenses against I predati-on in a subtidal marine community. Ecology 63:1599-1601.

I Schroeter, S.C. 1988. Origin and biological effects of a cohesive, fine sediment in the San Onofre kelp forest. Report to the I Marine Review Committee, Inc. In preparation. Schroeter, S.C., J.D. Dixon, and J. Kastendiek. 1983. Effects of the starfish Patiria miniata on the distribution of the sea I urchin Lytechi-nuE anamesus in a southern California kelp forest. 0ecologia 56zL4L-L47 .

I Schroeter, S.C., J. D. Dixon, T.A. Dean, R.O. Smith, T.J. Herrlinger, L.E. Deysher, and F.R. Jacobsen. 1988a. Effects of the operation of SONGSUnits 2 and 3 on patterns of kelp recruitment I in the San Onofre kelp forest. Final rePort to the Marine Review Committee, Inc. dated February 16, 1988.

I Schroeter, S.C., J.D. Dixon, J.E. Hose, and R.O. Smith. I988b. Mass mortalities of sea stars in southern California caused by t a new marine Vibrio. Unpublished manuscript.

I Shaffer, J.A. 1986. The adult reproductive behavior and larval biology of Conus californicus. M.S. thesis, San I Francisco State Univ., San Francisco.

I Snedecor, G.W. and W.G. Cochran. L967. Statistical methods. 7th ed. Iowa State Univ. Press, Ames. 507 pp.

I Stewart-Oaten, A. 1986. The Before-After/Control-Impact-Pairs design for environmental impact assessment. Report to the I Marine Review €onrmittee, Inc. dated June 20, 1986. I Stewart-Oaten, A. , W.W. Murdoch, and K.R. Parlter. 1986. I Environmental Lmpact assessment: "pseudoreplication" in time? Ecology 67 :929-940.

t Tegner, M.J. and P.K. Dayton. L987. El Nino effects on southern California kelp forest communities. Adv. Ecol. Res. I L7 2243-279. I

I 51 I I I I I I TABLES I I I

52 I

I Table 1. Date and duration of benthic surveys I SURVEY DAYS DAYS BEGINNING ENDING MID LENGTH BETWEEN BETWEEN I SURVEY DATE DATE DATE (DAYS) SURVEYS STARTS

I 2 13N0V80 17NOV80 r5Nov80 5 3 14JAN81 27JAN81 21JAN81 L4 58 52 4 25MAR81 O6APR81 3 1MAR81 13 57 70 I 5 O8JUN81 17JUNB1 13JUN81 10 63 75 6 210CT81 05NOV81 290CT81 L5 L26 135 I 7 26JAN82 O2FEB82 3OJAN82 8 82 97 8 22APR82 13MAY82 03t{AY8z 22 79 85 9 29JUL82 3OAUG82 14AUG8 33 77 98 I 10 I8NOV82 29NOV82 24NOV8h L2 80 112 -dh' 11MAR83 26APR83 lej$,PR8 27 L22 133 I 190cT83 11NOV83 310CT8 24 L76 202 <-ri 24I.,IAY84 O5JUN84 3OI.,IAY8 13 183 zLB L4 06Nov84 27NOV84 r7NOV8t 22 ls4 L56 I 15 O5MAR85 22MAR85 18 98 119 15 24|,IAY85 O4JUN85 L2 63 80 t L7 020cT85 180cT85 L7 L20 13'1 192 1OFEB86 14FEB86 1zFEB85 5 115 131 193 031,1AR86 07t{AR86 05l,tAR86 5 136 L52 2A 27MAY85 13JUN86 O5JUN86 18 81 85 I 2L O5SEPS 5 11SEP86 O8SEP86 7 84 101 I 22 01DEC86 05DEC86 03DEC86 5 81 87

I Notes:

rNo I sample at SOKD; poor sea conditions. 2Aborted due to storms. 3Duration I calculated from Survey 1-7. I

I 53 I I

Table 2. Sample size by period for the various species and substrates I for which abundances were estimated as part of the study of I the effects of SONGSon large benthic organisms. I PREOPERATIONAL INTERIM OPERATIONAL I SPECIES PERIOD PERIOD PERfOD I Porifera: Tethya aurantia 10 I Cnidaria: Muricea californica 10 I Muricea fruticosa 10 Mollusca:

Astraea gibberosa 10 2 8 I Astraea undosa 10 2 8 Bursa californica 2 2 8 Calliostoma spp. 2 2 8 I Conus californicus 6 2 8 Crassispira semiinf lata 5 2 8 Cypraea spadicea 10 2 8 Haliotis corrugata IO 2 8 I Haliotis rufescens 10 2 8 Haliotis spp. 10 2 8 Hinnites giganteus 10 2 8 I Kelletia kelletii 10 2 8 Maxwellia gemma 2 z 8 Megathura crenulata 10 2 8 Mitra idae 6 2 I t Murexiella santarosana 2 2 8 Na.ssarius spp. 2 I 8 Norrisi-a norrisi. 10 2 8 I Ocenebra s:,p. z 2 8 Octopus spp. 2 2 8 Ophiodermella inermis 2 2 8 Pteropurpura festiva 2 2 8 I Pteropurpura macroptera 2 2 8 I I

I s4 I t

I Table 2 (cont.) PREOPERATIONALINTERIM OPERATIONAL I SPECIES PERIOD PERIOD PERIOD Phaeophyta(cont):

I Pterygophora californica 10 I Substrata: Bedrock 10 2 8 Reef 10 2 8 Boulder 10 2 8 I Cobb1e + Pebble 10 2 8 Sand 10 2 8 Boulder >50 cm 8 2 8 I Boulder 41-50 cm 8 2 8 Boulder 31-40 cm 8 2 I Cobble 21-30 cm 8 2 8 Cobble tt-20 cm 8 2 8 I Cobble 5-10 cm 8 2 8 I Pebble 1-5 cm 8 2 8 t I t t I I I I

I 56 I I

Table 3 Substrate classification. (Wentworth scale taken from t from Shepard, F. P. 1973. Submarine GeobEX, 3rd ed. I N.Y.:Harper & Row.) I u.s. c. DIAI.{ETER PHI WENTWORTH I DESIGNATION (lo{) ( -Locz(MM) SCALE t BOULDER BOULDER 300 -8.2 256 -8 I COBBLE L28 -7 COBBLE 64 -6 50 -5 .6 I 32 -5 L5 -4 PEBB[.8 PEBBLE 8 -3 4 -2 I 2 -1 _ _ qRANULE 1 0 tlz +t I SAND Ll4 +/ SAND 1/8 +l Ll L6 +la I Ll32 +J SILT Ll64 +$ SILT LlL28 +J I Llzss +$ I I I I I

I 57 t I

I Table 4. Date and duration of kelp recruitment surveys. I t SURVEY DAYS DAYS BEGINNTNG ENDING MID LENGTH BETWEEN BETWEEN I SURVEY DATE DATE DATE (DAYS) SURVEYS STARTS 1 21SEP81 200cr8 1 060cr8 I 30 t 2 15DEC8I 18JAN82 O1JAN82 35 56 85 3 24JUN82 27JVL82 11JUL82 34 L57 19I I 4 060cr82 280CT82 170CT82 23 7L 104 t 5 09ICAY83 27JUN83 O3JUN83 50 193 2Ls 6 25JUL83 19AUG83 O7AUG83 26 28 77 t 7 28NOV83 3oDEC83 14DEC83 33 101 L26 8 17l,tAY84 O5JUN84 27t'tLy84 20 t39 171 I 9 020cr84 300cr84 160CT84 29 119 138 10 28DEC84 14FEB85 21JAN85 49 59 87 I 11 01r,1AY85 15I.,1AY85 0814AY85 15 75 t24 L2 O9JUL85 OzAUG85 21JUL85 25 55 69

I 13 290cr85 17DEC85 23N0V85 50 88 LL2 I L4 2I},IAR86 O4APR86 28MAR86 15 94 143 15 1BJUN85 16JUL86 O2JULB6 29 75 89 I 16 06NOV86 19NUV85 13N0V86 L4 113 141 t I I

I 58 I I

Table 5. Average density (number / mt) of species selected for I BACIP analysis. Species which were counted during two or more preoperational surveys and which had an average density in the San Onofre kelp forest of at least I L I 10 m2 on one or more surveys were selected for further analysis. Station means over alI surveys during the preoperational and operational periods I are tabulated. t PREOPERATIONAL OPERATIONAL BK SMK SOKD SOKU BK SMK SOKD SOKU I Astraea undosa 0.00 0.02 0.02 0.01 0.03 0.39 0.08 0.01 I Calliostoma spp. 0.00 0.00 0.05 0 .L2 o.02 0.02 o.Lz 0.03 Conus californicus 0.60 0.66 2.9L 4.4L 1. 65 L.75 L.67 1.11 I Crassispira semiinf lata 0. 11 0.01 0. 10 0. 14 0. t7 0.04 0.07 0.03 Cypraea spadicea 0.16 0.07 0.03 0.07 0.02 0. t8 0.02 0.0s t Kelletia kelletii 0.88 2.50 2.90 2.87 0.79 2.27 L.44 1.00 Lytechinus anamesus 3.89 0.44 7 .89 8 .35 1.58 13.06 34.90 15.61

I Maxwellia gemma 0.06 0 .22 0.20 0.75 0.23 0.40 0. tl 0.10 I Mitra idae 0.20 0.05 0.32 0.74 0.72 0. 18 0.78 0.75 Murexiella santarosana 0.31 0.40 0. 17 0.40 o .57 0. 39 0.04 0.08 I Muricea californica 4.7 6 s .04 0.21 0. 17 8 .65 7.01 5 .27 1.51 Muricea fruticosa 1. 93 0.85 0.01 0.02 2.79 1.36 0.27 0.L2 t Nassarius spp. 0.09 0.20 0.72 0.34 0.07 0. 19 0.43 0.2L I Ocenebra spp. 0.01 0.05 0.05 0.00 0.02 0.02 0.00 0.01 Patiria miniata 0.06 0.06 0 .50 L.L2 0.03 0.08 0.26 0.08

Phragmatopoma t californica 0.00 0.03 0.02 0.03 0.04 1.00 0.8s 0. 12 I Pisaster giganteus 0.03 0. 14 0.00 0.03 0.01 0.04 0.01 0.01 Pteropurpura festiva 0.16 0.47 4.26 2.95 0.70 1. 03 L.29 0 . 80 t

I 59 I I I Table 5 (cont.) T PREOPERATIONAL OPERATTONAL I BK SMK SOKD SOKU BK SMK SOKD SOKU Strongylocentrotus I franciscanus o .t2 1.05 0. 19 0 . 04 0.04 1.20 0.00 0.0s S. purpuratus 0.17 L.37 0.05 0.14 0.03 l. 60 0 . 06 0. 08 I StyeIa montereyensis o.47 0.30 2.L3 0 .42 0. 11 0. 10 0.01 0.00 Tegula aureotincta 0.01 0.00 0.00 0. 16 0.00 0.0s 0.02 0.01 I Tethya aurantia 0.20 0.04 0.02 a .L2 0. 13 0.01 0.03 0.07 ltl I I t I I I I I I t

I 50 t I

Table 6. Effect of an urchin front at SMK on benthic invertebrates. t A moving aggregation of red urchins was first noted grazing on the study transects in September 1986. Surveys conducted prior to that time are defined as "Before"; all others are I "After". "Impact" quadrats are those that were affected by the urchin front; the unaffected quadrats are considered the "Control". Cases where P > 0.05 for the test of additivity and where P < 0.20 for the t-test are tabulated. I NI = number of surveys in the "Before" period; N2 = number t of surveys in the "After" period. AVERAGEDENSITY SERIAL (NUMBER/sQM) TRANS- ADDITI- CORRE- IMPACT CONTROL I FOR}'ATION NI N2 VITY TREND LATION BEFOREAFTER BEFOREAFTER P>T

I SPECIES = Astraea undosa LOG(X+.025) LZ 2 .87 .38 NS 0.10 0.48 0.06 0.99 .L4

I SPECIES= Crassispira semiinflata (X+ 0.07 .L4 I LoG . 025) .64 . sI UN 0.09 0.0s 0.05 SPECIES = Cypraea spadicea I NONE l5 .47 .20 NS 0.09 0. 15 0. 12 0.35 .08 SPECIES = Murexiella santarosana I LOG(X+ .025 ) .87 .72 NS 0.33 0.00 0.43 0.05 SPECIES = Nassarius spp. I LOG(X+ .025 ) .67 .44 NS 0. 19 0. 10 0. 16 0.00 .00

SPECIES = Pteropurpura festiva I Loc(X+0 ) .55 .90 NS 0. 60 0 .25 0. 84 0.20 .L7

SPECIES = Stye1a montereyensis I LOG(X+ .025 ) 16 2 .49 .59 NS 0. t5 0.03 0. 15 0.L7 .07 I I I

I 61 I I

Table 7. Effect of silt accumulation at SOKUon benthic invertebrates. I Large deposits of silt were first noted in October 1985. Surveys prior to that time are defined as "Before"; all otherS aie "After". "Impact" quadrats are thoSe that had I at least 257" cover of silt on one or more surveys; all others are "Control" quadrats. Cases where P > 0.05 for the test of additivity and where P < 0.20 for the t-test are tabulated. Nl = number of surveys in the "Before" period; N2 = number I of surveys in the "After" period. t AVERAGEDENSITY SERIAL (NUMBER/SQ M) TRANS- ADDITI- CORRE- IMPACT CONTROL I FORMATION Nl N2 VITY TREND LATION BEFOREAFTER BEFOREAFTER P>T I SPECIES= Conus californicus I NONE . 19 .87 NS 3 .40 0.41 4.08 0.39 .15 SPECIES= Kelletia kelletii I LOG(X+.025) 13 .16 .92 NS r.87 0.39 2.24 1. 13 .00

SPECIES = Maxwellia gemma I LoG(X+ . 025) .59 .84 NS 0.28 0.01 0.31 0.07 .04

SPECIES= Murexiella santarosana I LOG(X+ .A25) .57 .31 NS a.25 0.03 0. 14 0. 13 .03

I SPECIES= Patiria miniata LoG(X+0 ) L22 .3s .14 NS 0.60 0.06 o .66 0. 19 .00

I SPECIES = Tethya aurantia Loc(X+0 ) L2 4 . s0 .90 NS 0.09 0.0s 0. 13 0. 16 .00 I I t I

I 62 I l

I Table 8. Results of the BACIP analysis on various species of snails. The average deltas in the preoperational and operational periods were compared with a t-test (P > T). The deltas are the differences in the mean densities I of organisms at the impact and control stations on each survey. All quadrats were used in the analysis . Nl, N2 = Sample sizes for "Before" and "After" periods, I respectively. TREND= P-value for a test for a linear trend during the operational period. lt = Test for serial correlation in preoperational data was significant. t AVERAGEDENSITY (NUMBER/sQM) TRANS- IMPACT CONTROL I SPECIES CONTROL FOR},IATION TREND BEFOREAFTER BEFOREAFTER P>T I Archeogastropoda Calliostoma spp. SOKD NONE .26 0. 13 0.04 0.06 0. 14 .07 SMK NONE .33 0. 13 0.05 0.00 0.03 . 13 I BK NONE .03 0. 13 0.04 0.00 0.02 .03 TeguIa SOKD NONE .77 0. 16 0.02 0.00 0.04 .27 aureotincta SMK NONE 0. 16 0.01 0.00 0.06 .24 I BK NONE 0. 16 0.03 0.01 0.00 .43

I Mesogastropoda Cypraea spadicea SOKD LOG(X+0) .34 0.09 0.04 0.04 0.0s .27 SMK Loc(X+0) .39 0.07 0.04 0.05 0. ls .00 I BK LOc(X+0) .30 0.05 0.04 o .20 0.03 .02

I Neogastropods Conus californica SOKD LoG(X+ .O25) .4A 4.23 0.64 2.72 0.85 .04 SMK LoG(X+ .025) .22 4 .23 A.64 0.56 1.01 .00 I BK NONE // .46 4.4L 1. 11 0. 60 1. 65 .00 Cras s i-spira SOKD LOG(x+ 1) .52 0.14 0.04 0. 10 0.08 . il I semiinflata BK NONE .19 0. 14 0.03 0. li. 0. 18 .05 Kelletia kelletii SOKD LOG(X+ 1) .94 2.63 0.96 2 .64 L.34 .07 SMK LOc(X+ 1) .18 2.63 0 .96 2.2L 2.23 .00 I BK Loc (X+I) .08 2.5L 0.95 0.82 0.75 .01

Maxwellia gemma SOKD NONE .70 0.75 0.10 0.20 0. 11 .00 t SMK NONE .16 0.75 0. t0 0.23 0.39 .0r BK NONE .60 0.75 0.r0 0.06 0.23 .00

Mitra idae SOKD LOc(X+0 ) .96 0.56 0.43 0.29 0.52 .08 I SMK LOG(X+ .025 ) .07 0.57 0.46 0.04 0.14 . 16 BK LOG(X+ .025 ) .03 o.57 A.46 0. 13 0.5s .08

63 I

I Table 8. (cont. )

AVERAGEDENSITY I (NUMBER/sQM) TRANS- IMPACT CONTROL I SPECIES CONTROL FORMATION TREND BEFORE AFTER BEFORE AFTER P>T Murexiella SOKD NONE .08 0.40 0.09 0. 18 0.05 .04 santarosana SMK NONE .25 0.40 0.09 0.40 0.4s .06 I BK NONE .61 0.40 0.08 0.31 0.57 .08 Nassarius spp. SOKD NONE .19 0.34 0.24 0.73 0.50 .72 SMK NONE .56 0. 34 0 .2L 0.20 0.19 .s6 I BK NONE .28 0.34 0.2L 0.09 0.08 .53

Ophiodermella SOKD NONE .32 0.06 0.06 0.08 0.02 .07 I inermis SMK NONE .30 0.06 0.06 0.00 0.0r .72 BK NONE .23 0.06 0.04 0.0r 0.02 .24

Pteropurpura SOKD NONE .24 2.9s 0.80 4 .26 L.29 .85 I festiva SMK NONE .31 2.95 0.80 0.48 1.03 .01 t BK NONE .78 2.9s 0.80 0. 16 0.70 .00 I I I I I I I I

I 64 I l

I Tab1e 9. Results of the BACIP analysis on various species of snails. The average deltas in the PreoPerational and operational periods were compared with a t-test (P > T). The deltas are the differences in the mean densities of I organisms at the impact and control stations on each survey. Only quadrats not impactedby urchin fronts or heavy (>= 257" cover) deposits of silt were used in the I analysis. Nl, N2 = sample sizes for "Before" and "After" periods, respectively. TREND= P-value for a test for a I linear trend during the operational period. AVERAGEDENSITY (NUMBER/sqM) I TRANS- IMPACT CONTROL SPECIES CONTROL FORI"IATION TREND BEFORE AFTER BEFORE AFTER P>T t Archeogastropoda

Calliostoma spp SOKD NONE .32 0. 17 0.03 0.07 0. 15 .05 I SMK NONE .67 0. 17 0.06 0.00 0.04 .07 BK NONE .02 0. 17 0.04 0.00 0.03 .02

TeguIa SOKD NONE .L2 0.28 0.01 0.00 0.05 .2r t aureotincta SMK NONE .75 0.28 0.02 0.00 0. 10 .04

I Mesogastropoda Cypraea spadicea SOKD LOG(X+ .O25) .19 0. t1 0.07 0.03 0.02 .80 SMK LOG(X+,1) .63 0.13 0.09 0. 10 0.19 .03 I BK LOG(X+ .O25) .52 0.08 0.09 0.09 0.02 . t6

I Neogastropoda Conus californica SOKD LoG(X+ 1) .49 4.53 0.95 2.67 L.32 .00 SMK LOG(X+ .OZS) .34 4.48 0.60 0.58 0.86 .00 l BK Loc(x+ 1) .13 4.53 0.95 0.38 1.31 .00

Crassispira SOKD Loc(X+ 1) .86 0"14 0.02 0.10 0.08 .04 I semiinflata SMK LOG(Xr 1) .99 0. 14 0.03 0.01 0.07 .01 BK NONE .45 0. 14 0.01 0. 11 0. r8 .03

Kelletia kelletii SOKD LOG(X+ 1) .31 2.83 t.27 2.7L 1.43 .34 I SMK LOG(x+0 ) .26 2.53 t.24 2.07 2.A3 .00 BK LoG(X+0 ) .14 2.35 L.24 0.77 0.63 .31 I Maxwellia gernma SOKD NONE .76 0.78 0. 13 0.19 0. 12 .00 SMK NONE .67 0. 78 0. 13 0.18 0.28 .01 I BK NONE .60 0.78 0. t3 0.06 0.23 .00 l 65 t I

I Tab1e 9. (cont. )

I AVERAGEDENSITY (NUMBER/sQ M) TRANS- IMPACT CONTROL I SPECIES CONTROL FORMATION TREND BEFORE AFTER BEFORE AFTER P>T

Mitra idae SOKD LoG(X+ .O25) .85 0.67 0.33 o.29 0. s6 .04 I BK LOG(X+ .025) .11 0.67 0.33 0. 13 0.55 .05

Murexiella SOKD NONE .48 0.39 0.08 0. 16 0.05 .08 I santarosana SMK NONE .L4 0.39 0.08 0 .40 0.51 .06 BK NONE .73 0.39 0.07 o.32 0.58 . 10

Nassarius spp. SOKD NONE .13 0.36 0. 15 0.70 0.51 .96 I SMK NONE .15 0.36 0.18 0. 13 0.24 .08 BK NONE .87 0.36 0. 13 0.06 0.07 .50 t Ophioderrnella SOKD NONE .08 0.03 0.08 0.08 0.02 .10 inermis

Pteropurpura SOKD NONE .L4 4.03 0.91 4.53 1.33 .99 t festiva SMK NONE .26 4.03 0.91 0 .40 r. ls .00 t BK NONE .4L 4.03 0.91 0. 17 0.71 .00 I l I t I I I I 66 I I

I Table 10. Results of the BACIP analysis on various invertebrates other than snails. The average deltas in the preoperational and operational periods were compared with a t-test (P t T). The deltas are the differences in the mean t densities of organisms at the impact and control stations on each survey. All quadrats were used in the analysis. Nl, N2 = Sample sizes for "Before" and "After" periods, I respectively. TREND= P-value for a test for a linear trend during the operational period. lt = Test for serial I correlation in preoperational data was significant.

AVERAGEDENSITY I (NUMBER/sQ M) TRANS- IMPACT CONTROL I SPECIES CONTROL FOR},IATION TREND BEFORE AFTER BEFORE AFTER P>T Sponges I Tethya aurantia SOKDLOG(X+0) .75 0. 10 0.06 0.04 0.03 .45 SMK LOG(X+ 1) .68 0. L2 0.07 0.04 0.01 .78 t BK NONE .80 0. l3 0.08 0.20 0. t3 .46 Gorgonians I Muricea californica SMK LOG(X+.O25) .00 0.17 1. 10 4.99 6.86 .00 Muricea fruticosa SOKDNONE .27 0.03 0. 13 0.03 0.27 .04 t BK LoG(X+0) .31 0.03 0. 18 1.83 2.83 .00 l Sea Urchins Strongylo centrotus SOKD NONE .73 0. t4 0.08 0.05 0.06 .05 PurPuratus SMK LOG(X+.025) .00 0.13 0.06 L.29 L.L2 .36

I Lytechinus anamesus SOKD NONE II .10 8.35 15.51 7 .89 34.90 .00 sMK LoG(x+1)/i .00 7 .68 L5.37 0.35 r0.41 .00 I BK NONE .02 8.64 15.51 3 .89 r.58 .00 Tunicates t StyeIa SOKDLOG(X+ .O25) 0.30 0.01 L.37 0.02 .39 I montereyensis BK LoG(X+.025) .L9 o .29 0.00 0.41 0.12 .0r I I 57 I l t Tab1e 11. Results of the BACIP analysis on various invertebrates other than snails. The average deltas in the' preoperational and operational periods were compared with a I t-test (P > T). The deltas are the differences in the mean densities of organisms at the impact and control stations on each survey. Only quadrats not impactedby urchin fronts or heavy (t= 25% cover) deposits of silt were used in the I analysis. Nl, N2 = sample sizes for "Before" and "After" periods, respectively. TREND= P-va1ue for a test for a I Iinear trend during the operational period.

AVERAGEDENSITY l (NUMBER/sq M) TRANS- IMPACT CONTROL SPECIES CONTROLFORI.IATION TREND BEFORE AFTER BEFORE AFTER P>T

TeEhya aurantia SOKDLoc(X+0) .52 0. t3 0.L2 0.05 0.03 .62 sMK LOG(X+ I ) .22 0. L4 0.13 0.06 0.0r .2L I BK NONE .94 0. 15 0. 12 0.20 0. 13 .31

Muricea californica SMK LOG(X+0 .00 a.32 L.73 5.53 6.86 .00 T BK LOG(X+ I .00 0.32 1. 90 4.87 8.51 .07 Strongylocentrotus SOKDLOG(X+ t .04 0.20 0.02 0.05 0.07 .00 PurPuratus 3MK LOG(X+ .O25) .26 0. t8 0.01 0.67 0.78 .00 I BK LOG(X+ I ) .4L o.2L 0.03 0. 16 0.04 .35 Lytechinus anamesus SOKDNONE -.24 9 .2L 2L.49 8.s1 37.00 .00 I SMK LoG(X+0) .02 9.18 21.38 0. t8 10.75 .00 BK NONE .30 9.65 2L.49 3 .99 1.59 .00

StyeIa l montereyensis BK LOG(X+.025) .11 0.44 0.00 0.40 a.L2 .00 T t t t I I 68 I t t Table L2. Comparison of density estimates at the benthic survey station (SOKU) and at the kelp recruitment stations in the I upcoast, offshore portion of the San onofre kelp forest.

KELP BENTHIC I SPECIES DATE SURVEY SURVEY P>T

Calliostoma spp. 1981 1985 0. 17 0.00 0.37 0.187 Conus californicus 1981 0.44 3.93 0.83 0.000 1985 2. 18 0.07 0. sl 0.023 t Crassispira semiinflata 198I 1986 0.05 0.00 0.00 0.331 Cypraea spadicea 198I 4.22 0.03 o.96 0.059 1986 0.06 o.02 0.50 0.620 l Kelletia kelletii 198I 2.44 2.78 0.60 0. ssI 1986 0.56 o.77 0.82 0.4L4 Lytechinus anamesus 1981 L2.07 3.03 0.47 0. rs4 I L986 L4.94 L3.07 0.31 0.758 Maxwellia gemma 1981 1986 0. 11 a.02 0.07 0 .295 Mitra idae 1981 0.07 0. 15 0.99 0.326 I 1986 0.22 0. 17 0.35 0.730 Murexiella santarosana 198I 1986 0.00 0.00 T Muricea californica 1981 0.30 o.23 0.40 0.687 1986 3.11 o.4s 0.48 0.023 Muricea fruticosa 1981 0. 11 0.03 0.01 0.320 1986 0.22 0.00 0.20 0.041 t Nassarius spp. 1981 1986 0. 11 o.L2 0.10 0.9L7 Patiria miniata 1981 0. 93 0.75 0. ss 0.582 I L986 o.L7 0.07 0.92 0.367 Pteropurpura festiva 1981 1986 r-.39 0.80 0.35 0.188 Strongylocentrotus purpuratus 1981 0.04 0. 13 0.98 0.330 t 1986 0.05 0.05 0.07 0.941 Tegula aureotincta 1981 1986 0.00 0.00 l Tethya aurarrtia 1981 0.04 0. 10 0.04 0.3(i3 1986 0. 06 0. 10 0.55 0.585 I I I I 69 I

I TabIe 13. Comparison of density estimates at the benthic survey station (SOKD) and at the kelp recruitment stations in the downcoast, offshore portion of the San Onofre kelp t forest.

KELP BENTHIC t SPECIES DATE SURVEY SURVEY P>T

Calliostoma spp. 1981 1986 0.00 0.00 Conus californicus 198I 0.50 L.56 o.sg o.oor 1986 L.67 0.35 o.2L 0.038 I Crassispira semiinflata 1981 L986 0.00 0.05 0.43 0. t-50 Cypraea spadicea r981 0.00 0.00 1986 0.05 0.05 o.og o.ggr I Kelletia kelletii 198I L.22 2.L6 0.79 0.079 1986 L.Z2 r. 15 0. t6 0.877 Lytechinus anamesus 198I 19.00 10.61 0.29 0.203 I 1986 19.55 35.87 0.27 0.025 Maxwellia gemma 198I 1985 0.05 0.00 0.00 0.331 Mitra idae 1981 0. 17 o.26 0. s5 0.580 1986 0.28 0. 15 0.69 0.500 Murexiella santarosana 1981 1986 0.00 0.00 t Muricea californica 198I 0.00 0. 18 0.89 0.006 1986 L.67 2.85 0.67 0. I01 Muricea fruticosa 198I 0.00 0.00 1986 0.00 0.17 0.48 0.018 t Nassarius spp. 1981 1986 0.05 0.02 o.so o.ezo Patiria miniata 198I 0.22 0.39 0.91 0.367 I 1986 0.11 o.27 0.29 0.201 Pteropurpura festiva 198I 1986 1. 11 L.47 o.52 0.605 Strongy locentrotus purpuratus 1981 0.00 0.00 t 1986 0.00 0.00 :: Tegula aureotincta 1981 798(, 0.00 0.00 t Tethya aurantia 1981 0.00 0.03 0.00 O..32tr 1986 0.00 0.00 I I I I 70 I I

I Table 14. Comparison of density estimates at the benthic survey station (SMK) and at the kelp recruitment stations in the San Mateo kelp forest. The two kelp recruitment stations t which were located in a white urchin barrens were not included in the analysis.

KELP BENTHIC I SPECIES DATE SURVEY SURVEY T P>T t Conus californicus 198I o.46 0. 30 0.87 0.391 1986 0.40 0. 15 0. 13 0.275 Crassispira semiinflata 1981 1986 0. 13 0.00 0.00 0.334 I Cypraea spadicea 1981 0. 17 0.08 o.72 0.478 1985 0.20 0. 15 0.33 0.740 Kelletia kelletii 1981 0. 17 2.32 o.29 0.025 1985 0.60 1.87 0.75 0.000 I Lytechinus anamesus 198I 5.75 0.40 0.95 0.053 1985 24.53 8.30 0.70 0.016 Maxwellia gemma 1981 I 1985 0.20 0. 17 0. 19 0.847 Mitra idae 1981 0.00 o.02 0.00 0.323 1986 0. 13 0.07 0.49 0.624 t Murexiel Ia santarosana 1981 1986 0. 13 0.20 o.44 0.55s Muricea californica 1981 2.42 4 .47 0.45 0.015 1985 3 .60 5 .65 0.95 0.057 I Muricea fruticosa 1981 0.58 0.82 0.88 0.380 1986 0.80 1. 15 0.93 0.355 Nassarius spp. 1981 I 1986 0.00 0 .05 0.43 0. 160 Patiria miniata 1981 0.37 0.07 0.53 0. t38 1985 o.47 0. 17 0. 18 A.254 Pteropurpura festiva 1981 t 1986 o.47 0.05 0. 10 0.052 Strongylocentfotus purpuratus 1981 o.92 0. 90 0.02 0.980 1986 5.20 1.50 0..67 0. 115 T Tegula aureotincta 1981 1985 0.00 0.00 Tethya aurantia 198I 0. 13 0.05 o.97 0.338 I 1986 0.00 0.03 0.00 0.324 t t I I t 7L I T t I t FIGURES t I t T T T T I I I I I

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I I , I I t I I t t I OPIRATINGHISTO RY: UNITS1+2+3 POWIRGINTRATID t PREOPERATI ONAL OPERATI ONAL 10 IUU I f vtl x X 80 I 1 1n t! 6 ntl \J 6 -\tt-A F I z A An Ld + 1 v \t I t! ,) I L 1n 0_ I I 1n I n I t B. DISCHARGTVOLUMI I I DPtrnDtrPATlnt\l Al I I l\Lr./t Lt\r1ttVt\nL OPERATI ONAL 1a n I 12.0 I 11rr.rFl ., I o I1.0 1nrv.v ru I 10.0 I \ qru qn R n-] "'"1 8.0 I ( t"t 7.0l 7,0 r 6. 0l h tt c nl t! u.l 5.0 I 4. 0-' 4.0 l 1 J \ tl ,) r'1 /-. )n ,| I t. t.u I U. 0.0 76 77 78 79 80 B1 82 BJ 84 db 87 XX NATtr I u/-1 tL t 88 I I I OPIRATINGHIST0RY:UNITS 2+3 A POWERGTNERAIED I .tn PREOPERAII ONAL INTERIM OPIRATI ONAL IU 1nn a on t f B BO 1 x I 70 I b 60 L o 50 I F 4 40 z I! 3 30 O 2 t E 2A 1 Ld I 0- 10 I 0 O JAJO JA JO JA JO JAJOJAJO JA JO J I 1981 1982 1983 1984 1985 I \J>(tl DATE t B. DI SCHARGEVOLUME

{n n 10. PRIOPIRATI ONAL INTERIM OPTRAII ONAL IU.U I o 9.0 o B. 8.0 t 7. 7.0 r,r) 6. 6.0 (o 5. t o 5.0 5 +. 4.0 ? I t! 3.0 l 2. 2.0 oJ 1. 1.0 t 0. 0.0 I OJAJOJAJOJAJOJAJOJAJOJAJOJ 198 1 1982 1983 1sB4 198s 1986 I DATE

I 90 I I A. STRONGYLA CE I'ITROTU S F RAA/C/.SC/.VU,S I n tl 6.00 I 5.0 N 5.00 I 4.0 4.00 ?n t U.U t! 3.00 00 I onn 2.0 L.VU :) z I 1.0 I.UU I 0.0 nnn 0 AJOJAJOJAJOJAJOJAJOJAJOJ I 1981 1982 198i 1984 1985 1986 XXXNOI AFFECITD BY URCH IN FRONT t EIE€AFFECITD BY URCHI N FRONI I B. STRONGYLOCENTROTUSPURPUMTUS t 8.0 ann 7,0 /.UU N I 6.0 O. UU 5.0 '\ iltl v. 4,0 / nn I LJ CN 1n znn :l 2.A I z /-.UU 1.0 1nn I 0.0 nnn OJAJOJ AJOJAJOJAJOJAJOJAJOJ I 10R1 I vv I 1982 1983 1984 1985 1986 X)+x NOTAFFECIID BY URCH IN FRONT I EIBE] AFFECITDBY URCH IN FRONI

I 92 I I A. /,STRAEA I UNDOSA 1.8 1.80 ,t r: I tn r .0u N 1A 1.40 I 1.2 1.2A v. 1.0 1.00 t! 0.8 I m 0.80 0.6 U. OU :) nt I z u.+ 0.40 0.2 U, LU I 0.0 0.00 OJA JO JAJOJA J OJAJO JAJOJA JOJ I 1981 1982 1983 1984 1985 1986 X+O(NOI AFFECIED BY URCH IN FRONT T EIEIEAFFTCIID BY URCH IN FRONT I B. CYPRAEASPADICEA

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A. PATIRIAMINIATA I I ilr\ 0.60 il\ N 0.50 I NA 0.40 a n1 LJ 0.30 I m n) nln l I n1 z v. I 0.10 I 0.0 0.00 OJAJOJAJOJAJOJAJOJAJOJAJOJ I 198t 1982 198J 1984 I985 1986 x)e( NOTAFFECITD BY URCH IN FRONI I EIEIBAFFECTED BYURCH IN FRONI I B. SWELAMONTEREru'il^S/S

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Ld 1 O rJ \t I I a bJ 2 /U 0_ 4 I I IU I n OJA JO JAJOJA JOJA JO JA JOJAJO J I 1981 1982 1983 1984 1985 1986 )e(x < 25 z SILI er+B)= 25 z SILT I t 100 I I A. KELLETIAKELLETII I 6.0 6.00 5.0 5.00 I N 4.0 4.00 V. I Ll J.0 J. UU 00 I :l 2.00 Z I 1n 1.00 0.0 0.00 I OJAJO JAJOJA JO JAJO JAJOJA JOJ i981 t9B2 198J 1984 1985 1986 I x)e( < 25 %S ILT g1E1g>= 25 % SILI I B. TIUREXIELLASANTAROSANA

I 4.7 0.70 0.6 0.60 I N ntr U..J 0.50 I v. 0.4 0.40 I! I m 0.3 0.J0 :) z 0.2 0.20 I 0.1 U.IU I nn 0.00 OJAJO JAJOJA JO JAJO JA JOJ AJOJ I 198 1 1982 1983 1984 1985 1986 x+e+(< 25 7 SILI er+B I LO2 I I A. PATIRIAMINIATA I |.8 i.80 ,ti I l.o | .0u N 1A 1.40 I 1.2 1)n K. i.0 I.UU t! I m 0.8 0.80

l u.0 0.60 T z 0.4 0.40 0.2 0.20 t nn 0.00 I OJA JO JAJOJA J OJA JO JAJO JA JOJ 198't 1982 1983 1984 1985 1986 I x*x < 25 %SILT ei+B>= 25 %SILI I B. MAXWELLIAGEMMA

1n I l.t. I.UU ilv n qn l N NR 0.B0 u.t 0.70 v. u.o 0.60 I t! n6 m U. 3U NA 0.40 I f tl ( fr 1n z n1 V,L 0.20 I tt I U.IU nn 0.00 I OJAJOJAJOJAJOJAJOJAJOJAJOJ 198i 1982 198J 1984 1985 1986 I x+(x < 25 z SILT rrein)= 25 r, SILT I 104 I I I A. TETHYAAURANTIA

U,L a.23 I 0.? a.22 N 0.2 0.20 n tt tx I n U.IU U. u.l0 t U. 0.14 I LI n m 0.12 U. 0. i0 0.0 t l 0.08 Z 0.0 0.06 nn 0.04 I 0.0 0.02 0.0 0.00 I OJAJOJAJOJAJOJAJOJAJOJAJOJ 198 1 1982 1983 1984 1985 1986 t x)+x< 25 z SILI rrn€ )= 25 %SILI I B. LYTECHINUSANAME^SI/^S

I J0.0 0.00 t N 20.0 0.00 I v. Ld m I l 10.0 0.00 I z I nn 0.00 OJAJOJAJOJAJOJAJOJAJOJAJOJ I 198 1 1982 1983 1984 1985 1986 >o<+(< 25 % SILI E€€ )= 25 % SILI t 106 I t AVERAGTPERCENI COVER OF S I LT AI SOKSTAI IONS - I zF SURVIY9 NOVEMBER1986 ^ -500 n 500 1000 1500 2000

td -1 nn - 1t il I I C) z IJ E. l.l I t! -800 Lrl -800 tr I v.O -1lnn -1J00 o IY . J7. .. T l! ta a

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I PREOPERATI ONAL INTERIM OPERAII ONAL 6 60 I v. 5 50 t! o 4 40 I () zF 3 30 IJ I C) v 2 2A hJ I n 1 10 I 0 OJAJOJ AJOJAJOJAJOJAJOJAJOJ 1981 1982 1983 1984 1985 1986 I EEfl BK oeo sMKos+ s0KDo€€ soKU t DI FFERENCEBETWEEN SIAT I ON MEANS I PREOPIRATI ONAL INTERIM OPERAII ONAL v.4 40 t td aJ 30 O I zF' 20 td ()1 v. 10 I hJ TL 0 I 10 OJAJOJAJO JAJOJAJO JAJOJAJOJ I 198 1 1982 1983 1984 1985 1986 I E}EE SOKU-BK EEO SOKU-SMKO+9 SOKU-SOKD I LL2 I I I CALLIOSTOTIASPP. STATI ON MEANS

I PR[OPIRATI ONAL INTERIM OPIRATI ONAL n1 0, J5 I 0.J 0. 30 Nn 0. 25 I \n Ev 0.20 l!^ 1 T CNU .I 0.15 :)0 I z 0.10 I 0 n 0.05 I 0.0 0. 00 OJA JO JAJOJA JO JA JOJA JOJAJOJ 1981 1982 1gBJ 1984 1985 1986 I EEE BK o,eo SMKe-ee SOKD,o++ SOKU I DI FFERINCTBTIWIEN STAI I ON MTANS PRIOPIRAII ONAL INTTRIM OPIRATI ONAL I 0.22 il .22 a.17 .Un .17 n 1a u. tL N U t .U .07 \ 0.0 '. tl .02 L5lY^^ -tt v'v tl I Ll .03 nnnn-U.U = tl .08 .1,n1 -'r -u. I 0 17 t 7 -o.t U . td -u./-n.t 0.23 I -0 .2 .28 OJA JOJAJO JA JO JA JOJAJOJAJOJ I 198 l 1982 198J 1984 1gB5 i 986 t EEE SOKU-BK Oeo SOKU-SMKoo0 SOKU-SOKD I 114 I I I CALLIOSTOMASPP. SOKU - SOKD U NTRANSFORM ED

PREOPERATI ONAL OPERATI ONAL I o.4

o.z I D

I T o.o I A t -o.2 -o .4 I JULAO JANAl JULAl JULA2 .JANAs JANAs tJULA5 JANA6 JUL86 JAN87 SOKU - SMK UNTRANSFORMED

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L T o.o I A -o.2

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n)V.L I 0,22 N 0.20 I t \ 0.1o n1 i a u.l ? Ll n1 2 l rn x' .: = H.ln -\ U.U 8 o I 0.0.TA nn U,U z I 0.0 OJAJOJAJOJAJOJAJOJAJOJAJOJ T 198 1 1982 1983 1984 1985 1986 EEE BK O'eOSMK Oge S6KDO{+ S.KU

; DI FFERENCEBETWIIN STATI ON MEANS

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I -u. I 1n t O JA JO J A J O J A J O JA J O J A.JO JA J O J 198 1 1982 198J 1984 1985 1986 I EEf, SOKU_BKO€€ SOKU-SMKO+O SOKU_SOKD I 122 I I I TEGUAAUREOTINCTA SOKU - SOKD UNTRANSFORMED

PREOPERATI ONAL OPERAT I ONAL il o.4 l t I I .JULAO .JANE1 .'UL81 JANA2 JULA2 JANAs JAN85 .JULA5 .JANA6 .'ULA6 .JANA7 SOKU - SMK UNTRANSFORMED

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I I t a

I -o.2

,JULao JANAI JULaI JANa2 ,rUL83 JAN85 JANaS t UL85 JANE6 JULaG JANET t SOKU - BK UNTRANSFORMED t "-.-l.>REOPERATIONAL OPERAT I ONAL

9 o.z I F L T A t o.o

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JULAO .JANA1 JULAl JANA2 .JUL82 JANA3 JANAs JULA5 JAN86 JULA6 JAN87 I _ SOKU SMK U NTR,A.NSFO RM ED t PREOPERATI ONAL OPERATI ONAL t t

T -o.2

JAN8l JULAl JAN82 JULA2 .JAN83 .JANAs .JUL85 .IAN86 JULA6 .JAN87

I SOKU _ BK t t NO TEST I A.SSUMPTIONS NOT MET I t t L28 I t CYPRAEASPADICEA STATI ON MEANS

I PREOPTRATI ONAL INTIRIM OPTRATI ONAL 0,4 .+3 I 0.4 .40 N 0.3 .35 > I 0.3 .30 ; 0.2 .25 hj6 ) ccl"'' .2A = 0.1 .lc z 4.1 .10 I 0.0 .05 t 0.0 .00 OJAJOJAJOJAJOJAJOJAJOJAJOJ 1981 1982 1983 1984 1s85 1986 t EEf BK OeO SMK O-99 SSKD S'KU "." I DI FFERENCTBETWTTN STAT I ON MTANS PREOPERATI ONAL INTIRIM OPERATI ONAL U. U I 0. n U. U N -0. T > -0. U \ -0. 0a'-u . t !4 -0. LL] ^ - vr -].2. -U.n I z -u.7 -0. -0. t I

OJAJOJAJOJAJOJAJO JAJOJAJOJ I 1981 1982 198J 1984 1985 1986 I EEfl SOKU-BK Oeo SOKU-SMK€O SOKU-SOKD

I 130 t t I CYPRAEASPADICEA SOKU - SOKD Loc(x)

PREOPERATI ONAL OPERAT I ONAL I 1.2 o.8 t D o.4 E L T o.o A I -o.4 T -o.8 -1 .2 I JULao JANaI JuLat !,ANa2 JUL82 JANaS rrANas JULas JANaB JULa6 JANaT SOKU - SMK LOG(X)

PREOPERATI ONAL OPERATI ONAL I 1.2 o.8

t 0.4 o.o I -o.4 t -o.8 -1 .2 t .,ULEO JANEl JULAl JANEz JULE2 JANEs .'UL85 .'AN86 JULA6 JAN87 SOKU - BK Loc(x)

PREOPERATI ONAL OPERAT t ONAL I 1-2 o.8 t D o.4 E I T o.o A I -o .4 t -o.8 -1 .2 t JULEO JANaI JULat JANa2 JULa2JANas JANES JULas JANao.JULaG JANBT I L32 I I t CYPRAEASPADICEA STAI I I ON MEANS nn PREOPTRATI ONAL INTERIM OPERAII ONAL u.o .60

AT I tt t WrU trn N ,I u.+ .40 v.i? LI V.U ,30 T m l .24 ZA. t u. I . tu t 0.0 .UU OJA JOJA JO JA JOJA JOJAJO JAJOJ 198 1 1982 1983 1984 1985 1986 J EEfl BK eeg SMKOgO SgKDe++ S'KU T DI FFERENCEBTTWEEN STAT I ON MEANS PREOPTRATI ONAL n INTERIM OPIRATI ONAL a T U. tt tl nV. U .2 V. n .I N -0. t -0. .0 > I \-0 .2 0. -0. -0 a I l! -0. -0 A m^ q - v. -0 -1, -u.n -\ -0 .o t z -u. -0 -7 -0. -0 .8 -0. -0 .g -l 1 I I tl

OJAJOJAJOJAJOJAJO JAJOJAJOJ I 198 1 1982 1gBJ 1984 1985 1986 I EEfl SOKU-BK OOe SSKU-SMKO+O SOKU-SOKD I 134 I I I CYPRAEASPADICEA SOKU - SOKD LoG(X+O.O2s)

PREOPERATI ONAL OPERATI ONAL I 1.2 o.E T P o.4 L L T o.o A il -o.4 t -o .8 -1 .2

.JULAO JANAI .JULAl JANA2 .'ULA2 JANES .'ANAs .JULAs .JAN86 JULA6 .'AN87 I - SOKU SMK LoG(X+ 1 ) PREOPERATI ONAL OPERATI ONAL I 1.2 o.E t D o,4 E. L T o.o A t -o .4 I -o .8 -1 .2 I .rULE0 JAN8l JULaI JANa2 iruL82 IJANES JANES ,ruLEs .,ANE6 .JUL8o ,JANa7 soKU - BK LOG(X+O.O25)

PREOPERATI ONAL OPERAT I ONAL I 1.2 o.a I D o.4 L T o.o A t -o.4 -o.8

I -1 .2 I JULAO JANA' JULA1 .JANA2 JUL82 JAN85 JANAs JUL85 JULA6 JANAT I 135 I I I COffI/SCALIFORAIICLIS I STATI ON MEANS PREOPERATI ONAL INTERIM OPIRATI ONAL 7 I o I 5 + I 3 2 I ,| I I n OJAJOJAJOJ AJOJAJOJAJO JAJOJ 1981 1982 1983 1984 1985 1986 I EIEE BK OeO sMKo-€ SoKD*o SOKU I DI FFERINCEBITWEEN STAT I ON MTANS PREOPERATI ONAL INTERIM OPERATI ONAL I o I .fi 2 1 I I 0 -1 t -2 -J I A -t I OJAJOJAJOJAJOJAJO JAJOJAJOJ 198 1 1982 1983 1984 1985 1986 I EEE S0KU-BK O€O SOKU-SMKffi SOKU-SOKD I I 138 I I COA/I/SCALIF ARfflC t/-S SOKU - SOKD LOG(X+o. O2s)

PREOPERATI ONAL OPERATI ONAL I 1.2 I o.9 D o.6 L T o.5 I A -o.o I -o.3 -o.6 I JULSO r,ANal JULaI JANaZ JULa2.JANas JANaS JULas JANB6 JULa6 JANaT soKU - sMK LOG(X-FO.O25)

I PREOPERATI ONAL OPERATI ONAL 1.2 I 0.9 D o.6 L I T 0.3 -o. o t -o.3 -o.6 I TJULEO JANaI ,JULa1 ,JANE2 JULaz JAN85 JANBS JULBS JANa6 t ULa6 ,rANaT SOKU - SMK UNTRANSFORMED I PREOPERATI ONAL OPERATI ONAL 5.O

I 5.O D F L T 1.O I A I -1.O -5. O I JULSO JANAl JULAl JAN82 JULA2 JAN83 JAN85 JULAs JAN86 JULA6 JANAT t I 140 T I CO^II/SCALIFARAIICUS I STATI ON MEANS PREOPERATI ONAL INTERIM OPERATI ONAL I I I N 7 I 6 E. 5 ld I m +

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I PREOPTRATI ONAL INTERIM OPERATI ONAL I 7 I 6 5 + I ? 2 a I I 0 -1 -t I -z -2 I -3 -+ I OJAJOJAJOJAJOJAJOJAJOJAJOJ 198 1 1982 1gBJ 1984 1985 1986 I EEE SOKU-BKOEE SOKU-SMKOOO SOKU-SOKD I r42 I I I CO.V[/,SCALI F ORAIIC t/S - SOKU SOKD LoG(x+ 1)

PREOPERATI ONAL OPERATI ONAL I 1.2 o.9

I P o.6 L L T o.J I A -o. o I -o.5 -o.6 I .TULAO .rANEt JULEI ,rAN82 ,JULa2 .rANaS .JANas JUL85 JANA6 .JUL86 JANET SOKU - SMK LoG(X+o.o2s)

PREOPERATI ONAL OPERATI ONAL I 1.2

0.9

I D o.6 L T o.3 A I -o, o I -o.3 -o.6 T .rUL8OJANEI,rULal JANa2,JULaZ ITANESrrAN8s,JUL65,JANE6,JULaO,JANE7 - SOKU BK Loc(x-F 1)

PREOPERATI ONAL JPERAT I ONAL I 1.2 o.s I D o.6 L T o.3 A t -o. o -o.3 I -o.6 I JULAO JANAl JULAl JAN82 JULA2 JAN85 JANA5 JULA5 JANA6 JULA6 JANAT t L44 I I I Cft/SS/,SP/fi/ SE l,flllt F LATA I STATI ON MTANS PREOPERATI ONAL illTERlMOPERATI ONAL I 0,3I .33 0,3I I .30 I B o.zt .25 ) o.trl ,20 trl^ t I I m u.l tr .15 = 0.1 z -1 .10 I 0,0 .05 I 0.0 .00 OJAJOJAJOJ AJOJAJOJAJOJ AJOJ I 1981 1982 1983 1984 1985 1986 EEE BK OeO SMK O,* SOKDE++ SOKU I DI FFERENCEBETWEEN STAT I ON MEANS PREOPERATI ONAL INTERIM OPERATI ONAL I 0. 0 0. 0 0.1l 0 I N -0. \rlni > -0. 1i \ -0. 2) I o<-0. 3l u-n +l 0 >m -x'X'5l 0 I -) -U. Gi 0 1l = -0. l1 -0. -0. I -1. T JAJO.J AJOJAJOJAJO JAJOJAJOJ 198 1 1982 1983 1984 1985 1986 I EEf S0KU-BK O€O SOKU-SMKO+9 SOKU-SOKD I L46 I CR/^SSISP/R,4 SE ][ I I NF LATA - SOKU SOKD Loc(x+ 1)

PREOPERATI ONAL OPERATI ONAL 1.O

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PREOPERATI ONAL OPERATI ONAL a -

JULsO JAN81 JULAl JANAz JULE2 JANAs JANA5 JULAs JANAS JULA6 JANAT

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PREOPERATI ONAL OPERATI ONAL I 1.O

I o.5

I o.o I -o.5 I .JUL8O.JANAl .,UL81 JULA2 .JANA3 .JANAs .JULAs ,JANE6 .'ULA6 .JANA7 Loc(X{- 1) I PREOPERATI ONAL OPERATI ONAL I

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I J I 2 1 I I 0 OJAJOJAJOJAJOJAJOJAJOJAJOJ I 1981 1982 1983 1984 1985 1986 E}Ef BK G€O SMK E# SOKDO+O SOKU t DIFFERTNCEBETWEEN STATION MEANS PREOPTRAT I I ONAL INTERIM OPERATI ONAL + 3 I N 2

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I o.5 D L T o.o I A t -o.5

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I o.5 D L T o.o I A I -o.5 -1.O

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I PREOPERATI ONAL OPERATI ONAL t o.5

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I PREOPERATI ONAL OPERATI ONAL

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I PREOPERATI ONAL OPERATI ONAL 2-O

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I PREOPERATI ONAL OPERATI o.5 ONAL

I o.o I -o.5 t -1.O

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T PREOPERATI ONAL OPERATI ONAL o.5 t o.o I -o.5 I -1 .O -1 .5 I JULAO JANAl JULSl JANA2 JULA2 JANAS JANAs JULAS JAN86 JULA6 JANAT t 180 t I t ]TI] RE XI E LLA S AI{ TAft O S/AI/ I STATI ON MEANS

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I ^l PREOPTRATI ONAL INTERIM OPERATI ONAL 0.11 0.o C.u 0 i I 0.21 0.2 N -0. Gi .0 > -0.21 ,2 t \ -0.u A o:-c. 6l .o -9.8l .8 H 0-1 I -!. .0 = 2,1 .2 A z-1 . .'t -1. .6 I -t.1 .8 t -2. .0 OJAJOJAJOJAJOJAJO JAJOJAJOJ 1981 1982 1983 1984 1985 1986 I EIEE SOKU-BK OeO SoKU-SMKO+O SOKU-SOKD l t L82 I t 1,1iJRE XIE LLA S AN TARO SAN A SOKU - SOKD UNTRANSFORMED

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L I T o.o a*- T I A a t -o .5 I -1 .O t JULEO,JANSl ,,ULA1 JANa2 JULa2,JANESJANES JULaS JAN86,JUL86 JAN87 SoKU - BK UNTRANSFORMED t PREOPERATI ONAL OPERATI ONAL 1.O t o.5 D E L T o.o t A I -o.5 -1 .O I JULAO JANA' JULAl JANAz JULAz JANA3 JAN85 JULAs JAN86 JULA6 JANAT T 188 I T T lr/ss/ft/t/ssPP. I SIAT I ON MTANS PREOPERATI ONAL INTERIM OPERATI ONAL I 2.0 2.00 1.8 1.80 N 1.6 1.60 I 1,+ 1.40 1.2 1.24 E. 1nn T IJ 1.0 m 0.8 0.80 l 0.6 0.60 t z 0.4 0.40 4.2 0.2a { 0.0 0.00 t' OJA JOJAJ OJA JO JAJOJA JO JA JOJ 1981 1982 1983 1984 1985 1986 EEE BK eeo sMKoso soKDeo+ soKU DI FFERENCEBTTWEEN STAT I ON MEANS

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190 t t OP HI O DE RT,IE LLA INE RT,il S SOKU - SOKD U NTRANSFORMED

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I .JULAO JANA 1 JULAl .JANA2 .JULA2 .JANAS .JANAs JULA5 JANA6 JULA6 .'ANA7 I SOKU - SMK uoc(x+ r ) PREOPERATI ONAL OPERATI ONAL 2.5 I 2.O P 1.s F L t T 1.O A o.5 I o.o -o .5 I JULAO JANEl T,ULA1 JANAz 'JULAz 'JANEs JANES 'JULE5 JANE6 JUL85 JANET t SOKU - BK UNTRANSFORMED PREOPERATI ONAL OPERAT I ONAL 27 I 1A 9 I o -9 t -18 -27

I JULAO JANAl JUL81 JANA2 JULA2 JAN85 JAN85.'ULAs JANA6 JULA6 JANAT I 240 I I I LYTECHINUSANAMT'SIIS I STATI ON MTANS PREOPERATI ONAL INTERIM OPERATI ONAL l A NI I \3 E. l! T c0? f I z1 I OJAJOJAJOJAJOJAJOJAJOJAJOJ 1981 1982 1983 1984 1985 1986 I EIEE BK O€O SMKOOO SoKDO€+ S0KU t DI FFERENCTBETWEEN STAT I ON MEANS PRIOPERATI ONAL INTERIM OPERATI ONAL I 3 30 2 20 I N 10 E t hl 0 m >-1 f 10 t z.} -L 20 I -3 30 I OJAJOJAJOJAJOJAJO JAJOJAJOJ 198 1 1982 1983 1984 1985 1986 I EIEIESOKU-BK OOO SoKU-SMKOO€' SoKU-SoKD I 242 I I I LYTE C H I N U S A]{ AMT'S I/S SOKU _ SOKD U NTR,ANSFORM ED t I pREopERATToNAL OPERATI ONAL ar1 .'"1I t I D -lol F I r Lla-' ' T OJ 1 I Al r. -s'ilr * -18i I I I -27 I t JULEO JAN81 JULA 1 JANA2 .JUL82 JAN83 JAN85 JULAS JAN86 .JULA6 .JANA7 SOKU - SMK Loc(x)

i pREopERATr oNAL OPERATI ONAL I 2.s1 lf ^^l 2.r,1 l* I t_ I P 1 .5-..1 LI 1.0-l r AlT I I 0.sl I o.o-l I I -o.5 t. - I JULEO JANAl JULAl JAN82 JULS2 JAN85 .JAN85 JULES JAN86 .JULA6 JAN87 SOKU - BK UNTRANSFORMED

I pREopERATtop41 OPERATI t ''1^-l ONAL I 18J I I ^l t U 9J * Fl .' tI - inl - . vl i I AI -9 l -18 -27 I JULSO JANAl JULAl JANA2 JUL82 JANAS JAN85 JULA5 JAN86 JULA6 JAN87 I 244 I t I STYE LA I,l ANTE RI'ru' rSIS t STATI ON MTANS I PREOPERATI ONAL INTERIM OPERATI ONAL

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OJAJOJAJOJ AJOJAJOJ AJOJAJOJ t 198 1 1982 1985 1984 1985 1986 t EIEIBBK OeO SMK SOKD9++ SoKU DI FFERENCEBETWEEN STAT I ON MEANS

I PREOPERATI ONAL INTERIM OPERATI ONAL l I t -2 T -3 t -4 OJAJOJAJOJAJOJAJO JAJOJAJOJ 198 1 1982 1gBJ 1984 1985 1986 I ElEf, SoKU-BK O€O S0KU-SMK SOKU-SOKD I 246 I t t STY ELA II 0]\t T E Rg fE.\iS/S I LOG(X+O.O2s) PREOPERATI ONAL OPERATI ONAL I I l I t SOKU - SMK T NO TEST I ASSUMPTIONS NOT t MET I -BK -r LOG (X O. O2s )

t PREOPERATI ONAL OPERATI ONAL I T I

I JAN85 JULAS JANA6 JULA6 JAN87 I 248 I I I STY ELA l,l 0 N T E RI' ru'ffS/S I STAII ONMEANS t PRTOPERATI ONAL INTERIM OPERATI ONAL I N v. UJ T m l I z t OJAJOJAJOJAJOJAJOJAJOJAJOJ 1981 1982 198J 1984 1985 1986 I EIEE BK O€O sMK O'OOSSKD .*+ S'KU DI FFERENCEBETWEEN STAT I ON MEANS

I PRIOPERATI ONAL INTERIM OPERATI ONAL 2

I I N I 0 v. -l ,| LtJ m I -2 f z t -3 -4

I OJAJOJAJOJAJOJAJOJAJOJAJOJ 1981 1982 1983 1984 1985 1986 I EElf, SoKU-BKo€o SoKU-SMKoo0 SOKU-S0KD

I 2so I I I STYE LA fuI AN T E RT' ru'ffS/S I SOKU - SOKD t l NO TEST ASSU T M PTIONS NOT M ET I t SOKU - SMK t I NO TEST t ASSUMPTIONS NOT MET T - I SOKU BK LOG (X -Fo. Ozs) PREOPERATI ONAL OPERATI ONAL o.6 t o.5 D o.o L T -o.5 t A -o.6 I -o.9 -1 .2 l JULEO JANAl JULAl JANA2 JUL82 JANAS JAN85 JUL85 JANA6 JULA6 JANAT I 252 I I t I '1 I APPENDIXA T t I I I t T I I T I t t t I t Appendix A-1. Results of tests of the a.ssumptions underlying the t-test used in the BACIP analysis. All quadrats were used in the analysis. Nl, N2 = sample sizes for "Before" and "After" periods, r'espectively. TREND= linear trend in T the "Before" period. SERIAL TRANS- ADDITI- CORRE- t SPECIES CONTROL FOR}'IATION Nl N2 VITY TREND LATION

Astraea undosa SOKD LOG(X+ .025) 88 .43 .00 SIG I Astraea undosa SOKD LOG(X+0) 22 UNK Astraea undosa SOKD LOG(X+1) 88 .40 .00 SIG I Astraea undosa SOKD NONE 88 .40 .00 SIG Astraea undosa SMK LOG(X+ .025) 78 .91 .02 SIG Astraea undosa SMK LOG(x+0) 33 .00 .99 UNK Astraea undosa SMK LOG(X+1) 78 .37 .02 SIG I Astraea undosa SMK NONE 78 .34 .02 SIG

Astraea undosa BK LoG(X+.025) 36 .46 UNK t Astraea undosa BK LOG(x+0) 01 Astraea undosa BK LOG(x+1) 36 .00 .46 UNK Astraea undosa BK NONE 36 .46 UNK l Calliostoma spp. SOKD LoG(X+ .O25) 27 UNK Calliostoma spp. SOKD LoG(X+0) 24 UNK Calliostoma spp. SOKD LOG(x+1) 2.7 UNK I Calliostoma spp. SOKD NONE 27 UNK Calliostoma spp. SMK LoG(X+ .02s ) 2 5 UNK Calliostoma spp. SMK LoG(x+0 ) 0 2 I Calliostoma spp. SMK LoG(x+ 1) 2 5 UNK Calliostoma spp. SMK NONE 2 5 UNK T Calliostoma spp. BK LoG(X+ .025 ) 2 7 UNK Calliostoma spp. BK LoG(X+ 0 ) 0 I Calliostoma spp. BK LoG(x+ 1) 2 7 UNK t Calliostoma spp. BK NONE 2 7 : : UNK Conus ealifornicus SOKD LOG(X+.025) 5 8 .53 .08 NS Conus californicus soKD LOG(x+0) 5 8 .52 .08 NS I Conus californicus SOKD LOc(x+1) 5 8 .66 .07 NS Conus californicus SOKD NONE 6 8 .61 .05 NS

Conus californicus SMK LoG(X+ .025 ) 6 8 .L4 .10 NS I Conus californicus SMK LOG(X+0 ) 6 8 .13 .11 NS Conus californicus SMK LoG(X+ 1) 6 I .94 .03 NS t Conus californicus SMK NONE 6 8 .01 .38 NS Conus californicus BK LoG(X+ .025) 6 8 .00 .20 NS Conus californicus BK LOG(X+0 ) 5 8 .02 .35 NS Conus californicus BK LOG(x+ 1) 6 8 .07 .26 NS I Conus californicus BK NONE 6 8 .50 .11 SIG I 254 I I t Appendix A-1 (cont.) SERIAL I TRANS- ADDITI- CORRE- SPECIES CONTROL FORMATION Nl N2 VITY TREND LATION

I Cras s i spira semiinflata SOKD LOG(X+.025) 57 .23 .64 NS Crassispira semiinflata SOKD LOG(x+0) 43 .92 .07 NS Crass ispira semiinflata SOKD LOG(X+L) 57 .76 .23 NS I Cras s i spira semiinflata SOKD NONE 57 .82 .20 NS Crassispira semiinflata SMK LoG(X+ .02s ) 55 .4L .03 NS Crass ispira semiinflata SMK LOG(X+0 ) T2 UNK I Crassispira semiinflata SMK Loc(X+ 1) 55 .28 .02 SIG Cras s i spira semiinflata SMK NONE 55 .22 .02 SIG

Crassispira semiinflata BK LoG(X+ .025) 58 .26 .25 NS r (x+0 53 .19 .27 NS Crassispira semiinf lata BK LoG ) Crassispira semiinf lata BK LoG(X+ 1) 58 .42 .28 NS t Crassispira semiinflata BK NONE 58 .43 .29 NS Cypraea spadicea SOKD LOG(X+ .025) 98 .30 .05 SIG Cypraea spadicea SOKD Loc(X+0) 64 .83 .36 NS t Cypraea spadicea SOKD LOG(x+1) 98 .83 .20 SIG Cypraea spadicea SOKD NONE 98 .85 .22 SIG

Cypraea spadieea SMK LoG(X+ .O25) 98 .87 .13 NS I Cypraea spadicea SMK LOG(X+0) 98 .92 .15 NS Cypraea spadicea SMK LOG(x+ 1) 98 .70 .10 NS I Cypraea spadicea SMK NONE 98 .68 .10 NS Cypraea spadicea BK LOG(X+ .025) 98 .04 .18 NS Cypraea spadicea BK LoG(X+ 0 ) 54 .38 .s4 NS Cypraea spadicea BK LOG(X+ 1) 98 .00 .L7 NS I Cypraea spadicea BK NONE 98 .00 .17 NS Kelletia kelletii SOKD LoG(X+ .025) 10 8 .20 .08 NS Ke1letia kel let ii SOKD LOG(X+0) 10 8 .15 .08 NS I Ke1 let ia kelletii soKD LOG(X+1) 10 8 .94 .L4 NS Kel Ietia kel let ii SOKD NONE 10 8 .60 .13 NS I Ke1 let ia keI 1et ii SMK LOG(X+.025) 10 8 .23 .07 NS KeI let ia ke 1let ii SMK LoG(X+0) L0 8 .18 .07 NS Ke1 let ia kelletii sMK LoG(X+ 1) 10 8 .93 .L2 NS t KeI let ia kel let ii SMK NONE 10 8 .32 .28 NS Ke1letia ke1 let ii BK LOG(X+ .025) 9 I .08 .09 NS KeI let ia ke 1let ii BK LOG(X+0) 9 8 .07 .10 NS I Kel letia ke1 let ii BK LOG(X+1) 9 8 .14 .11 NS Ke1 let ia ke1 Iet ii BK NONE I 8 .07 .26 NS I t 255 I I t Appendix A-1 (cont.) SERIAL t TRANS- ADDITI- CORRE- SPECIES CONTROL FORMATION Nl N2 VITY TREND LATION t Lytechinus anamesus SOKD LoG(X+.025) 10 8 .25 .38 SIG Lytechinus anamesus SOKD LOG(X+0) 10 I .25 .38 SIG Lytechinus anamesus SOKD LOG(X+1) 10 8 .30 .43 SIG T Lytechinus anamesus SOKD NONE 10 8 .52 .81 SIG Lytechinus anamesus SMK LoG(X+.O25) 10 8 .00 .31 SIG Lytechinus anamesus SMK LOG(x+0 ) 5 8 .07 .23 NS t Lytechinus anamesus SMK LOG(x+ 1) 10 8 .65 .51 SIG Lytechinus anamesus SMK NONE 10 8 .00 .10 NS I Lytechinus anamesus BK LoG(X+ .025 ) 98 .00 .05 SlG Lytechinus anamesus BK LoG(X+0 ) 88 .04 .24 NS Lytechinus anamesus BK LOG(x+ 1) 98 .05 .L4 NS I Lytechinus anamesus BK NONE 98 .54 .72 NS Maxwellia gemma SOKD LoG(X+ .O25) 28 UNK Maxwellia genrma SOKD LOG(X+0) 27 UNK I Maxwellia genma SOKD LoG(X+1) 28 UNK Maxwellia gemma SOKD NONE 28 UNK

Maxwellia gemma SMK LOG(X+ .O25) 28 UNK I Maxwellia gemma SMK LoG(X+0) 27 UNK Maxwellia gemma SMK LoG(X+1) 28 UNK t Maxwellia gemma SMK NONE 28 UNK Maxwellia gemma BK LOG(X+ .A25) 28 UNK Maxwellia gemma BK LOc(X+0) 18 UNK Maxwellia gemma BK LOG(x+ 1) 28 UNK I Maxwellia genma BK NONE 28 : UNK

Mitra idae soKD LoG(X+ .O25) 68 .28 .47 NS I Mitra idae SOKD LoG(x+0) 68 .32 .46 NS Mitra idae SOKD LOG(x+1) 68 .05 .58 NS Mitra idae SOKD NONE 68 .01 .55 NS

I Mitra idae SMK LoG(X+ .OZS) 58 .52 .42 NS Mitra idae SMK LOG(X+0 ) 57 .50 .74 NS Mitra idae SMK LoG(X+ 1) 68 .00 .48 NS T Mitra idae SMK NONE 68 .00 .57 NS Mitra idae BK LoG(X+ .025 ) 68 .63 .78 NS Mitra idae BK LOG(X+0 ) 58 .68 .04 SIG I Mitra idae BK LoG(X+ 1) 68 .T7 .45 NS NONE 58 .03 .51 NS I Mitra idae BK T 256 I I

I Appendix A-1 (cont.) SERIAL I TRANS- ADDITI- CORRE- SPECIES CONTROL FOR}'IATION Nl N2 VITY TREND LATION

I Murexiel Ia santarosana SOKD LoG(X+ .O25) 27 UNK Murexiel 1a santarosana SOKD LOG(x+0) 24 UNK Murexiel la santarosana SOKD LOG(X+1) 27 UNK I Murexiel 1a santarosana SOKD NONE 27 UNK Murexiel la santarosana SMK LOG(X+.025) 27 UNK Murexiella santarosana SMK LOG(x+0) 25 UNK I Murexiel la santarosana SMK LoG(x+ 1) 27 UNK Murexiella santarosana SMK NONE 27 UNK

Murexiel la santarosana BK LoG(X+.025) 28 UNK I Murexiella santarosana BK LoG(X+0) 24 UNK Murexiel la santarosana BK LoG(x+ 1) 28 UNK I Murexiel la santarosana BK NONE 28 : UNK Muricea californica SOKD LOG(X+ .O25) 108 .00 .29 NS Muricea californica SOKD LOG(X+0) 108 .00 .33 NS Muricea californica SOKD LoG(X+1) 108 .00 .16 NS I Muricea californica SOKD NONE 108 .00 .L4 NS

Muricea californica SMK LoG(X+ .025 ) 108 .27 .34 NS I Muricea ealifornica SMK LOG(X+0 ) 108 .L4 .4L NS Muricea californica SMK LoG(x+ 1) 108 .00 .03 NS Muricea californica SMK NONE 108 .00 .01 SIG

I Muricea californica BK LoG(X+ .O25) 98 .03 .53 NS Muricea californica BK LoG(X+0 ) 98 .01 .55 NS Muricea californica BK LoG(X+ 1) 98 .07 .30 NS I Muricea californica BK NONE 98 .00 .26 NS

Muricea fruticosa SOKD LoG(X+ .O25) 5 I .24 .24 NS Muricea fruticosa SOKD LOG(x+0) 4 5 .63 .27 NS I Muricea fruticosa SOKD LOG(X+1) 6 8 .80 .11 NS Muricea fruticosa SOKD NONE 6 8 .84 .11 NS I Muricea fruticosa SMK LoG(X+ .Ozs) 10 I .01 .30 NS Muricea fruticosa SMK LOG(X+0 ) 6 5 .06 .26 NS Muricea fruticosa SMK LoG(X+ 1) 10 8 .00 .66 NS I Muricea fruticosa SMK NONE 10 8 .00 .78 NS Muricea fruticosa BK LoG(X+ .A25) 9 I .04 .98 NS Muricea fruticosa BK LOG(X+0 ) 5 5 .2t .64 NS I Muricea fruticosa BK LoG(X+ 1) 9 8 .00 .13 NS Muricea fruticosa BK NONE 9 8 .00 .10 NS I I t 257 I

I Appendix A-1 (cont.) SERIAL I TRANS- ADDITI- CORRE- SPECIES CONTROL FOR},TATIONNI N2 VITY TREND LATlON

I Nassarius spp. SOKD LoG(X+ .A25) 27 UNK Nassarius spp. SOKD LoG(X+0 ) 16 UNK Nassarius spp. SOKD LoG(X+ 1) 27 UNK I Nassarius spp. SOKD NONE 27 UNK Nassarius spp. SMK LOG(X+ .025 ) 28 UNK Nassarius spp. SMK LoG(X+0 ) 17 UNK I Nassarius spp. SMK LoG(x+ 1) 28 UNK Nassarius spp. SMK NONE 28 UNK I Nassarius spp. BK LoG(X+ .02s) z8 UNK Nassarius spp. BK LoG(X+0 ) 15 UNK Nassarius spp. BK LoG(x+ 1) 28 UNK I Nassarius spp. BK NONE 28 UNK Ophiodermella inermis SOKD LoG(X+ .025 ) 25 UNK Ophiodermella inermis SOKD Loc (X+0) 23 UNK t Ophiodermella inermis SOKD LoG(X+ 1) 25 UNK Ophiodermella inermis SOKD NONE 25 UNK

Ophiodermella r-nermt-s SMK LoG(X+ .O25) 25 UNK I 0phiodermella inermis SMK LOG(X+0 ) 02 Ophiodermella inermis SMK LoG(X+ 1) 25 UNK I Ophiodermella inermis SMK NONE 25 UNK Ophiodermella inermis BK LoG(X+ .025 ) 27 UNK Ophiodermella inermis BK LoG(x+0 ) 12 UNK Ophiodermella inermis BK LOG(X+ 1) 27 UNK I Ophiodermella inermis BK NONE 27 UNK

Parastichopus parvimensi SOKD LoG(X+ .025) 25 UNK I Parastichopus parvimensi SOKD LoG(x+0 ) 12 UNK Parastichopus parvimensi SOKD LoG(X+ 1) 25 : UNK Parastichopus parvimensi SOKD NONE 25 UNK

I Parastichopus parvimensi SMK LoG(X+ .02s ) 10 8 .27 .80 NS Parastichopus parvimensi SMK LoG(X+0 ) 2 3 UNK Parastichopus parvimensi SMK LoG(x+ 1) 10 I .00 .68 NS I Parastichopus parvimensi SMK NONE 10 8 .00 .66 NS Paras t i chopus Parvlmensl BK LoG(X+ .025 ) 9 8 .01 .25 NS Parastichopus parvimensi BK LOG(X+0 ) 1 3 UNK t Parastichopus parvimensi BK LoG(x+ 1) 9 I .00 .49 NS parvimensi 9 8 .00 .58 NS I Parastichopus BK NONE I t 2s8 il

I Appendix A-1 (cont.) SERIAL I TRANS- ADDITI- CORRE- SPECIES CONTROL FORI,IATION Nl N2 VITY TREND LATION

I Pteropurpura festiva SOKD LOG(X+.025) 2 8 UNK Pteropurpura festiva SOKD LoG(X+0) 2 8 UNK Pteropurpura festiva SOKD LOG(X+1) 2 8 UNK I Pteropurpura festiva SOKD NONE 2 I UNK Pteropurpura festiva SMK LOG(X+ .025) 2 8 UNK Pteropurpura festiva SMK LoG(X+0) 2 8 UNK I Pteropurpura festiva SMK LOG(x+ 1) 2 8 UNK Pteropurpura festiva SMK NONE 2 8 UNK I Pteropurpura festiva BK LoG(X+ .AZ5) 2 8 UNK Pteropurpura festiva BK LOG(X+0 ) 1 8 UNK Pteropurpura festiva BK LoG(x+ 1) 2 8 UNK I Pteropurpura festiva BK NONE 2 8 UNK S. purpuratus SOKD LOG(X+ .O25) 10 8 .02 .37 NS S. purpuratus SOKD LOG(X+0) 7 3 .06 .zo NS I S. purpuratus SOKD LoG(x+1) 10 8 .92 .46 NS S. purpuratus SOKD NONE 10 8 .88 .54 NS

S. purpuratus SMK LOG(X+ .02s ) 10 8 .95 .15 NS I S. purpuratus SMK Loc (x+0 ) 10 7 .68 .19 NS S. purpuratus SMK LoG(X+ 1) 10 8 .00 .42 NS I S. purpuratus SMK NONE 10 8 .00 .01 NS S. purpuratus BK LoG(X+ .025) 9 7 .00 .99 NS S. purpuratus BK Loc (x+0 ) 8 5 .02 .88 NS S. purpuratus BK LoG(X+ 1) 9 7 .01 .45 NS t S. purpuratus BK NONE 9 7 .01 .37 NS

Styela montereyensis SOKD LoG(X+ .025) 10 2 .22 .L7 NS I StyeIa montereyensis SOKD LoG(X+0) 10 0 .49 .34 NS StyeIa montereyensis SOKD LoG(X+1) 10 2 .00 .00 SIG Styela montereyensis SOKD NONE 10 2 .00 .00 SIG

I StyeIa montereyensis SMK LoG(X+.025) 10 8 .04 .01 SIG Styela montereyensis SMK LOG(X+0 ) 10 1 .03 .01 SIG Styela montereyensis SMK LOG(X+ 1) 10 8 .07 .00 SIG I Styela montereyensis SMK NONE 10 I .06 .00 SIG Styela montereyensis BK LoG(X+ .OZ5) 9 6 .31 .L4 NS Styela montereyensis BK LOG(X+0 ) 9 I .35 .L7 NS I Styela montereyensis BK LoG(x+ 1) 9 6 .20 .05 SIG 9 6 .L7 .03 slG I Styela montereyensis BK NONE I I 259 I

I Appendix A-1 (cont.) SERIAL TRANS- ADDITI- CORRE- I SPECIES CONTROL FOR},IATION Nl N2 VITY TREND LATlON

I Tegula aureotincta SOKD LOG(X+.025) 2 4 UNK Tegula aureotincta SOKD LOG(X+0) 0 3 Tegula aureotincta SOKD LOG(X+1) 2 4 UNK I Tegula aureotincta SOKD NONE 2 4 UNK Tegula aureotincta SMK LoG(X+ .025 ) 2 6 UNK Tegula aureotincta SMK LOG(X+0 ) 0 2 I Tegula aureotincta SMK LOc(X+ 1) 2 6 UNK Tegula aureotincta SMK NONE 2 6 UNK I Tegula aureotincta BK LoG(X+ . 025 ) 2 3 UNK Tegula aureotincta BK LOG(X+0 ) 1 0 UNK Tegula aureotincta BK LOG(X+ 1) 2 3 UNK I Tegula aureotincta BK NONE 2 3 : : UNK Tethya aurantia SOKD LOG(X+ .025) 10 8 .01 .01 NS Tethya aurantia SOKD LoG(X+0) 5 7 .15 .27 NS Tethya aurantia SOKD LOG(X+1) 10 8 .92 .00 SIG I Tethya aurantia SOKD NONE 10 8 .73 .00 SIG

Tethya aurantia SMK LoG(X+ .025) 10 8 .L7 .13 NS I Tethya aurantia SMK LoG(X+0) 10 2 .04 .15 NS Tethya aurantia SMK LOG(X+ 1) 10 I .61 .08 NS Tethya aurantia SMK NONE 10 8 .46 .08 NS

I Tethya aurantia BK LoG(X+.025) 9 8 .58 .13 NS Tethya aurantia BK LOG(x+0 ) 9 8 .46 .11 NS Tethya aurantia BK LOG(X+ 1) 9 8 .69 .27 NS I Tethya aurantia BK NONE 9 8 .56 .30 NS I I I I I t 260 I I

I Appendix A-2. Results of tests of the assumptions underlying the t-test used in the BACIP analysis. Only quadrats not impacted by urehin fronts or heavy (t= 25% cover) deposits of silt were used in the analysis. I Nl, N2 = sample sizes for "Before" and "After" periods, respectively-. TREND= linear trend in the "Before" period. SERIAL I TRANS- ADDITI- CORRE- SPECIES CONTROL FOR},IAT]ON Nl N2 VITY TREND LATION I Astraea undosa SOKD LOG(X+ .O25) 88 .20 .00 SIG Astraea undosa SOKD LOG(X+0) 22 UNK Astraea undosa SOKD LOG(x+1) 88 .L4 .00 SIG I Astraea undosa SOKD NONE 88 .L4 .00 SIG

Astraea undosa SMK LoG(X+ .025) 58 .50 .04 NS I Astraea undosa SMK LoG(x+0 ) 22 UNK Astraea undosa SMK LoG(x+ 1) 58 .23 .02 NS Astraea undosa SMK NONE 58 .2L .42 NS

I Astraea undosa BK LoG(X+ .OZS) 36 UNK Astraea undosa BK LOG(x+0 ) 01 Astraea undosa BK LoG(x+ 1) 36 UNK I Astraea undosa BK NONE 36 UNK Calliostoma spp. S0KD LoG(X+ .025) 27 UNK Calliostoma spp. SOKD LOG(x+0) 23 UNK I Calliostoma spp. SOKD LOG(x+1) 27 UNK Calliostoma spp. SOKD NONE 27 UNK I Calliostoma spp. SMK LoG(X+ .025) 24 UNK Calliostoma spp. SMK LOG(x+0 ) 02 Calliostoma spp. SMK Loc (x+ 1) 24 UNK I Calliostoma spp. SMK NONE 24 UNK Calliostoma spp. BK LoG(X+ . 025 ) 25 UNK Calliostoma spp. BK Loc (X+0) 01 t Calliostoma spp. BK LoG(X+ 1) 25 UNK Calliostoma spp. BK NONE 26 : UNK

Conus californicus SOKD LOG(X+.025) 68 .90 .09 NS I Conus californicus SOKD LOG(X+0) 67 .91 .09 NS Conus californicus SOKD LOG(X+1) 68 .57 .16 NS I Conus californicus SOKD NONE 68 .05 .55 NS Conus californicus SMK LOG(X+ .025) 68 .78 .27 NS Conus californicus SMK LOG(x+0 ) 57 .66 .27 NS Conus californicus SMK LOG(x+ 1) 68 .02 .7L NS I Conus californicus SMK NONE 68 .00 .95 NS

Conus californicus BK LoG(X+.025) 68 .01 .24 NS I Conus californicus BK LOG(X+0 ) 57 .02 .40 NS Conus californicus BK LoG(X+ 1) 68 .19 .46 NS I Conus californicus BK NONE 58 .11 .73 NS 26L I I

I Appendix A-2 (cont.)

I SERIAL TRANS- ADDITI- CORRE- I SPECIES CONTROL FORMATION NI N2 VITY TREND LATION Crassispira semiinf lata SOKD LOG(X+ .025) 57 .35 "67 NS Crassispira semiinflata SOKD LOG(X+0) 42 .87 .22 NS I Crassispira semiinf lata SOKD LOG(x+1) 57 .89 .29 NS Crassispira semiinf lata SOKD NONE 57 .94 .26 NS

Crassispira semiinf lata SMK LoG(X+ .025) s4 .95 .05 NS I Crassispira semiinf lata SMK LOG(x+0) L2 UNK Crassispira semiinf lata SMK LoG(X+ 1) 54 .10 .09 NS I Crassispira semiinf lata SMK NONE 54 .07 .09 NS Crassispira semiinf lata BK LoG(X+ .025) 58 .29 .4L NS Crassispira semiinf lata BK LOG(x+0) 52 .23 .43 NS Crassispira semiinf lata BK LoG(X+ 1) 58 .41 .40 NS I Crassispira semiinf lata BK NONE s8 .41 .4L NS

Cypraea spadicea SOKD LOG(X+.025) 98 .69 .22 NS I Cypraea spadicea SOKD LoG(X+0) 53 .02 .4L NS Cypraea spadicea SOKD LOG(X+1) 98 .11 .64 NS Cypraea spadicea SOKD NONE 98 .08 .68 NS

I Cypraea spadicea SMK LOG(X+ .025) 98 .78 .80 NS Cypraea spadicea SMK LOG(X+ 0 ) 57 .61 .42 SIG Cypraea spadicea SMK LOG(x+ 1) 98 .90 .89 NS I Cypraea spadicea SMK NONE 98 .86 .88 NS Cypraea spadicea BK LOG(X+ .025) 9 7 .45 .24 NS Cypraea spadicea BK LOG(x+0 ) 4 4 .41 .54 NS I Cypraea spadicea BK LoG(X+ 1) I 7 .31 .20 NS Cypraea spadicea BK NONE 9 7 .28 .zo NS I Kelletia kelletii SOKD LoG(X+.025) 10 I .46 .23 NS Kelleria kelletii SOKD LoG(X+0) 10 8 .43 .23 NS Kelletia kelletii SOKD LOG(X+1) 10 8 .65 .27 NS I Kelletia kelletii SOKD NONE 10 8 .66 .24 NS Kelletia kelletii SMK LOG(X+ .025) 10 8 .87 .54 NS Kelletia kelletii sMK LOG(X+0) 10 8 .87 .54 NS t Kelletia kelletii sMK LOG(x+ 1) 10 I .80 .54 NS Kelletia kelletii SMK NONE 10 I .43 .63 NS

Kelleria kellerii BK LoG(X+.025) 9 8 .L2 .09 NS I Kelletia kellerii BK LOG(X+0 ) 9 8 .L2 .09 NS KeIletia kelletii BK LOG(x+ 1) 9 8 .13 .L4 SIG I Kelletia kelletii BK NONE 9 8 .03 .38 NS I t 262 I

I Appendix A-2 (cont.)

I SERIAL TRANS- ADDITI- CORRE- I SPECIES CONTROL FORI'{ATION NI N2 VITY TREND LATION Lytechinus anamesus SOKD LoG(X+.025) 10 8 .62 .64 src Lytechinus anamesus SOKD LoG(X+0) 10 I .62 .64 SIG I Lytechinus anamesus SOKD LOG(X+1) 10 8 .68 .74 SIG Lytechinus anamesus SOKD NONE 10 8 .92 .89 STG

Lytechinus anamesus SMK LoG(X+ .025 ) 10 8 .08 .92 NS I Lytechinus anamesus SMK LoG(x+0 ) 4 8 .85 .65 NS Lytechinus anamesus SMK LoG(X+ 1) 10 8 .00 .15 SIG I Lytechinus anamesus SMK NONE 10 8 .00 .06 SIC Lytechinus anamesus BK LoG(X+ .025) 98 .01 .08 SIG Lytechinus anamesus BK Loc (x+0 ) 88 .10 .40 NS Lytechinus anamesus BK LOG(X+ 1) 98 .15 .25 NS I Lytechinus anamesus BK NONE 98 .92 .90 NS

Maxwellia gemma SOKD LOG(X+.025) 28 UNK I Maxwellia gemma SOKD LOG(X+0) 27 UNK Maxwellia gemma SCKD LOG(X+1) 28 UNK Maxwellia gemma SOKD NONE 28 : UNK

I Maxwellia gemma SMK LOG(X+.025) 28 UNK Maxwellia gemma SMK LOG(x+0 ) 27 UNK Maxwellia gemma sMK LOG(X+1) 28 UNK I Maxwellia gemma SMK NONE 28 UNK Maxwellia gemma BK LOG(X+ .A25) 28 UNK Maxwellia gemma BK LOG(x+0) 18 UNK I Maxwellia genma BK LoG(X+ 1) 28 UNK Maxwellia gemma BK NONE 28 : UNK I Mitra idae SOKD LoG(X+.A25) 68 .2L .33 NS Mitra idae SOKD LOG(X+0) 67 .24 .33 NS Mitra idae SOKD LOG(X+1) 68 .03 .38 NS I Mitra idae SOKD NONE 68 .00 .47 NS Mitra idae SMK LOG(X+ .OZ5) 68 .4s .02 SIG Mitra idae SMK LoG(x+0 ) 45 .L6 NS I Mitra idae SMK LOG(X+ 1) 68 .00 .23 NS Mitra idae SMK NONE 58 .00 .35 NS

Mitra idae BK LOG(X+ .025) 68 .65 .63 NS I Mitra idae BK Loc (x+0 ) 57 .62 .02 SIG Mitra idae BK Loc (X+1) 58 .09 .2L NS I Mitra idae BK NONE 68 .01 .31 NS I 263 I I

I Appendix A-2 (cont.)

I SERIAL TRANS- ADDITI- CORRE- I SPECIES CONTROL FORI.{ATION Nl N2 VITY TREND LATION Murexiella santarosana SOKD LoG(X+.025) 27 UNK Murexiella santarosana SOKD LOG(X+0) 24 UNK I Murexiella santarosana SOKD LOG(X+ 1) 27 UNK Murexiella santarosana SOKD NONE 27 UNK

Murexiella santarosana SMK LoG(X+ .025) 27 UNK I Murexiella santarosana SMK LOG(x+ 0 ) 25 UNK Murexiella santarosana sMK LOG(X+ 1) 27 UNK I Murexiella santarosana SMK NONE 27 UNK Murexiella santarosana BK LoG(X+ .025) 28 UNK Murexiella santarosana BK LOG(X+0) 24 UNK Murexiella santarosana BK LOG(x+ 1) z8 UNK I Murexiel la santarosana BK NONE 28 : UNK

Muricea californica SOKD LoG(X+ .025) 108 .01 .4L NS t Muricea californica SOKD LoG(X+0) 108 .00 .4s NS Muricea californica SOKD LOG(X+1) 108 .01 .20 NS Muricea californiea SOKD NONE 108 .00 .17 NS

I Muricea californica SMK LOG(X+.025) 108 .46 .18 NS Muricea californica SMK LoG(X+0 ) 108 .60 .20 NS Muricea californica SMK LoG(X+ 1) 108 .00 .03 NS I Muricea californica SMK NONE 108 .00 .02 NS Muricea californica BK LOG(X+.025) 98 .06 .50 NS Muricea californica BK LOG(x+ 0 ) 98 .04 .51 NS I Muricea californica BK LoG(X+ 1) 98 .26 .32 NS Muricea californica BK NONE 98 .00 .27 NS I Murieea frutieosa SOKD LoG(X+.025) 4 8 .7L NS Muricea fruticosa SOKD LOG(x+0) 0 5 Muricea fruticosa SOKD LOG(x+1) 4 8 .7L NS I Muricea fruticosa SOKD NONE 4 8 .7L NS Muricea frutieosa SMK LoG(X+.025) 10 8 .00 .48 NS Muricea fruticosa sMK LOG(X+0) 0 5 I Muricea fruticosa SMK LOG(x+ 1) 10 8 .49 NS Muricea fruticosa SMK NONE 10 8 .50 NS

Muricea fruticosa BK LOG(X+ .OZ5) 9 I .07 NS I Muricea fruticosa BK LOG(X+0) 0 5 Muricea fruticosa BK LoG(X+ 1) 9 8 .00 .07 NS t Muricea fruticosa BK NONE 9 8 .08 NS I t 264 I

I Appendix A-2 (cont. )

SERIAL I TRANS- ADDITI. CORRE- Nl N2 VITY TREND LATION I SPECIES CONTROL FOR},IATION Nassarius spp. SOKD LoG(X+ . 025 ) 27 UNK Nassarius spp. SOKD LOG(x+0 ) 15 UNK Nassarius spp. SOKD LoG(X+ 1) 27 UNK I Nassarius spp. SOKD NONE 27 UNK

Nassarius spp. SMK LoG(X+ .025 ) 26 UNK I Nassarius spp. SMK LoG(X+0 ) 15 UNK Nassarius spp. SMK LoG(X+ 1) 26 UNK Nassarius spp. SMK NONE 26 UNK

I Nassarius spp. BK LoG(X+.025) 28 UNK Nassarius spp. BK LoG(x+0 ) 14 UNK Nassarius spp. BK LoG(X+ 1) 28 UNK I Nassarius spp. BK NONE 28 UNK

Ophiodermella inermis SOKD LoG(X+ .025 ) 24 UNK Ophiodermella inermis SOKD LOG(X+0 ) 12 UNK I Ophiodermella inermis SOKD LoG(x+ 1) 24 UNK Ophiodermella inermis SOKD NONE 24 UNK

I Ophiodermella inermis SMK LOG(X+.O25) 14 UNK Ophiodermella inermis SMK LoG(x+ 0 ) 01 Ophiodermella inermis SMK LoG(x+ 1) 14 UNK I Ophiodermella inermis SMK NONE L4 UNK Ophiodermella inermis BK LoG(X+.O25) 15 UNK Ophiodermella inermis BK LOG(X+0 ) 02 I Ophiodermella inermis BK LoG(X+ 1) 15 UNK Ophiodermella inermis BK NONE 15 UNK

Parastichopus parvimensi SOKD LoG(X+ .O25) 24 UNK I Parastichopus parvimensi SOKD LoG(x+0 ) 02 Parastichopus parvimensi SOKD LoG(x+ 1) 24 UNK I Parastichopus parvimensi SOKD NONE 24 UNK Parastichopus Parvr-mensL SMK LoG(X+ .O25) 10 8 .04 .61 NS Paras t i chopus parvimensi SMK LOG(x+0 ) I 2 UNK t Parastichopus parvimensi SMK LoG(X+ 1) 10 8 .08 .48 NS Parastichopus parvimensi SMK NONE 10 8 .42 .38 NS

Parastichopus parvimensi BK LoG(X+.O25) 9 8 .00 .19 NS I Parastichopus parvimensi BK LOG(X+ 0 ) 0 2 Parastichopus parvimensi BK LOG(X+ 1) 9 8 .00 .4L NS I Parastichopus parvimensi BK NONE 9 8 .00 .49 NS t 265 I I

I Appendix A-2 (cont.)

I SERIAL TRANS- ADDITI- CORRE- I SPECIES CONTROL FORI.,TATION Nl N2 VITY TREND LATION Pteropurpura festiva SOKD LOG(X+ .025 ) 28 UNK Pteropurpura festiva SOKD LOG(x+0) 28 UNK Pteropurpura festiva SOKD LOG(X+1) 28 UNK I Pteropurpura festiva SOKD NONE 28 UNK

Pteropurpura festiva SMK LoG(X+ .025) 28 UNK I Pteropurpura festiva SMK LOG(X+0 ) 27 UNK Pteropurpura festiva SMK LoG(X+ 1) 28 UNK I Pteropurpura festiva SMK NONE 28 UNK Pteropurpura festiva BK LOG(X+ .025 ) 28 UNK Pteropurpura festiva BK LOG(X+0 ) 18 UNK Pteropurpura festiva BK LoG(x+ 1) 28 UNK I Pteropurpura festiva BK NONE 28 UNK

S. purpuratus SOKD LOG(X+.025) 10 7 .27 .37 NS I S. purpuratus SOKD LOG(X+0) 7 0 .53 .26 NS S. purpuratus SOKD LOG(X+1) 10 I .4L .49 NS S. purpuratus SOKD NONE 10 7 .28 .59 NS

I S. purpuratus SMK LoG(X+ .O25) 10 8 .86 .07 NS S. purpuratus SMK LOG(X+0 ) 10 3 .81 .09 NS S. purpuratus SMK LoG(x+ 1) 10 I .01 .02 NS I S. purpuratus SMK NONE 10 I .00 .02 NS S. purpuratus BK LOG(X+ .025) 9 6 .05 .87 NS S. purpuratus BK LOc(X+0 ) 8 2 .L9 .76 NS I S. purpuratus BK LoG(X+ 1) 9 6 .11 .58 NS S. purpuratus BK NONE 9 6 .10 .48 NS

Styela montereyensis SOKD LOG(X+.025) 10 1 .09 .L2 slG I Styela montereyensis SOKD LoG(X+0) 10 0 .13 .L6 NS Styela montereyensis SOKD LOG(x+1) 10 1 .00 .00 slG I Styela montereyensis SOKD NONE 10 I .00 .00 SIG StyeIa montereyensis SMK LoG(X+ .O25) 10 5 .05 .00 SIG Styela montereyensis SMK LOG(X+0) 10 0 .47 .00 SlG Styela montereyensis SMK LOc(x+1) 10 5 .00 .00 SIG I Styela montereyensis SMK NONE 10 5 .00 .00 SIG

Styela montereyensis BK LOG(X+.025) 9 6 .53 .20 NS I Styela montereyensis BK LOG(x+0) 9 0 .58 .26 NS StyeIa montereyensis BK LOG(X+ I ) 9 6 .08 .03 SIG Styela montereyensis BK NONE o 6 .02 .01 SIG I s I 266 I I

I Appendix A-2 (cont.)

I SERIAL TRANS- ADDITI- CORRE- I SPECIES CONTROL FORI.{ATION N1 N2 VITY TREND LATION TeguIa aureotincta SOKD LOG(X+ .O25) 2 4 UNK Tegula aureotincta SOKD LOG(X+0) 0 1 I TeguIa aureo'tincta SOKD LOG(X+1) 2 4 UNK Tegula aureotincta SOKD NONE 2 4 UNK

Tegula aureotincta sMK LOG(X+ .O25) 2 3 UNK I Tegula aureotincta SMK LOG(x+0 ) 0 I Tegula aureotincta SMK LOG(x+ 1) 2 3 UNK I Tegula aureotincta SMK NONE 2 3 UNK Tegula aureotincta BK LoG(X+ .025) 2 1 UNK TeguIa aureotincta BK LOG(x+0) 1 0 UNK Tegula aureotincta BK LOG(X+ 1) 2 1 UNK I Tegula aureotincta BK NONE 2 1 . UNK

Tethya aurantia SOKD LOG(X+ .O25) 10 I .02 .01 NS T Tethya aurantia SOKD LOG(X+0) 4 6 .44 .64 NS Tethya aurantia SOKD LOG(X+1) 10 8 .64 .02 NS Tethya aurantia SOKD NONE 10 8 .45 .02 NS

I Tethya aurantia SMK LOG(X+.025) 10 7 .08 .32 NS Tethya aurantia SMK LOG(X+0) 9 2 .47 .19 NS Tethya aurantia SMK LOG(x+ 1) 10 7 .79 .15 NS I Tethya aurantia SMK NONE 10 7 .64 .15 NS Tethya aurantia BK LOG(X+ .O25) 9 8 .20 .24 NS Tethya aurantia BK LoG(X+0) 9 7 .L7 .23 NS I Tethya aurantia BK LOG(x+ 1) 9 8 .39 .31 NS Tethya aurantia BK NONE 9 8 .44 .33 NS I I t I I I 267 I I I I

APPENDIXB: FLOWCHARTS OF COMPUTERPROGRAMS I USEDTO PRODUCETHE TABLESAND FIGURES I I I I I I I I I I I I t I I Intermediate data bases. Flow chart fo.r intermediate data bases used in flow charts listed on the following Pages. I $p*e-"- p"t"SL) I I DBBENT.SUROz - DBBENT.SUR22 AU o&*vi4 i"tt BENTMEANSAS BENTMN2SAS BENTMN3SAS DBBENTMN.SURVO222 DBBENTMz. SURVO222 DBBENTM3. SURVO222

I MKBACDBSSAS I I DBBACICT. ALLQUAD DBBACICT. NOIMPACT DBBACICT.IMPACTED DBBACICT.COMBINED BTEST1 SAS BTEST4 SAS BTEST2 SAS BTESTs SAS BTEST3 SAS BTEST6 SAS

DBBACTST. ALLSUSK DBBACTST. NOISUSK DBBACTST. ALLSUSD DBBACTST.NOISUSD DBBACTST. ALLSUBK DBBACTST. NOISUBK DBASSUMP. ALLSUSK DBASSUMP.NOISUSK DBASSUMP. ALLSUSD DBASSUMP. NOISUSD DBASSUMP. ALLSUBK DBASSUMP.NOISUBK I I I I I I CONCAT SAS

DBASSUME. ALLQDCNT I DBASST'ME. NOIMPCNT DBBACTST. ALLQDCNT I DBBACTST.NOIMPCNT I t 269 I

I Table 1. Date and duration of benthic surveys.

I Constructed by hand from data notebooks. I Table 2. Sample size by period for the various species and substrates for which abundances were estimated as part of the study of I the effects of SONGSon large benthic organisms. I DBBENT.SURO2 - DBBENT.SUR22 t BENTMEANSAS DBBENTMN.SURVO222 I CNT_TABL SAS I Tab1e 2.

I Table 3. Substrate classification. (Wentwort h scale taken from from Shepard, F. P. L973. Submarine Geology, 3rd ed. I N.Y. :Harper & Row.) I Constructed by hand.

I Table 4. Date and duration of kelp recruitment surveys. I Constructed by hand from data notebooks. I I I I 270 I t

I Table 5. Average density (number I ^2 ) of species selected for BACIP analysis. Species which were counted during two or more preoperational surveys and which had an average density t in the San Onofre kelp forest of at least L / 10 m2 on on one or more surveys were selected for further analysis. Station means over all surveys during the preoPerational I and operational periods are tabulated. t DBBENT.SURO2- DBBENT.SUR22 BENTMEANSAS

I DBBENTMN.SURVO222 I SPMEANSAS Tab1e 5. I I I I I t t I I I I 27L I I

Table 6. Effect of an urchin front at SMK on benthic invertebrates. t A moving aggregation of red urchins was first noted grazLng on the study transects in September 1986. Surveys conducted prior to that time are defined as "Before"; all others are t "After". "Impact" quadrats are those that were affected by the urchin front; the unaffected quadrats are considered the "Control". Cases where P > 0.05 for the test of additivity and where P < 0.20 for the t-test are tabulated. I Nl = number of surveys in the "Before" period; N2 = number of surveys in the period. I "Aftert' DBBACICT.COMBINED(See intermediate data base flow diagram)

I URSILTDB SAS I DBIMPACT.URFRONT BACTTEST EXEC (URCHBACTMACROCAL) I DBASSUM.URFRONT DBBTEST.URFRONT t MKDBURSLSAS DBURFRNT.FORTABL I URFTTABL SAS I Table 6. I t I I I I I I 272 t

I Table 7. Effect of an urchin front at S.OKUon benthic invertebrates. A moving aggregation of red urchins was first noted grazi-ng on the stuai tiansects in September 1986. Surveys conducted prior to that time are defined as "Before"; all others are I i'After". "Impact" quadrats are those that were affected by the urchin fr-ont; the unaf fected quadrats are considered the "Control". Cases where P > 0.05 for the test of additivity l and where P < 0.20 for the t-test are tabulated. Nl = number of surveys in the "Before" period; I N2 = number of surveys in the "After" period. I DBBACICT.COMBINED(see intermediate data base flovr diagram) URSILTDBSAS I DBIMPACT.SILT BACTTESTEXEC (STLTBACTI{ACROCAL)

I DBASSUM.SILT DBBTEST.SILT t MKDBURSLSAS DBSILT. FORTABL

I SILTTABL SAS l Table 7. t t I T I I t 273 I I

I Tables 8-11. Results of BACIP anayses on various species of snails (Tables 8 and 9) and species other than snails (Tables 10 and 11). The average deltas in the PreoPerational and operational periods were compared with a t-test (P > T). I The deltas are the differences in the mean densities of organisms at the impact and control stations on each survey. All quadrats were used in the analyses for Tables 8 and 10. I Only quadrats not impacted by urchin fronts or heavy (t= 25% eovet) deposits of silt were used in analyses for Tables 9 and 11. Nl, N2 = sample sizes for "Before" and "After" periods, respectively. TREND= P-value for a test for a t linear trend during the operational period. # = test for data was significant. I serial correlation in operational DBASSUM.ALLQDCNT (See intermediate data base flow DBASSUM.NOIMPACT chart for these data bases. ) DBBACTST. ALLQDCNT I DBBACTST. NOIMPACT I DBBTTABL SAS DBALLDAT.BACTABL DBNOIDAT.BACTABL t SELECTSAS

DBSELECT. ALLQUADS t DBSELECT.NOIMPACT TESTTABL SAS

I Tables 8, 9, 10, and 11. t I t t I I I 274 I I t

I Tables L2-L4. Comparisons of density es.timates between the SOKUbenthic survey station and the kelp recruitment stations in the upcoast, offshore portion of the San Onofre kelp forest (Table LZ); between the SOKDbenthic survey station and the I kelp recruitmen.t stations in the downcoast, offshore portion of the San Onofre kelp forest (Table 13 ) ; and between the SMK benthic survey station and the kelp recruitment stations I in the San Mateo kelp forest (Table 14). The two SMKkelp recruitment .stations which were located in a white urchin t barrens were not included in the SMK analysis.

1. MINIMBOl DATA I MINIMBO2 DATA MINIMBSSAS DBMINIMB.SUROl DBMINIMB.SURO2 t MINIMBS2 SAS DBMINI.MACOlO2 T 2. DBBENT.SURO6 DBBENT.SURzO MKMINMBSSAS I DBMINI.MBSOlO2 3. DBMIN].I.,IACO1O2 I DBMINI.MBSOl02 MINITESTSAS t TTEST LISTING BENSUMDATA (values entered by hand) t TTSTTABL SAS I Tables L2, 13, and L4. I t I I I 275 T Appendix A. Flow chart for Appendix A.

DBALLDAT.BACTABL DBNOIDAT.BACTABL

ASSUMPTNSAS

APPENDIX A

276 I

I Figure 1. Study areas in the vicinity o.f the San Onofre Nuclear Generating Station. The rectangles are the boundaries of the detailed maps of the San Mateo kelp forest (S}'IK, Figure 2), the San Onofre kelp forest (SOK, Figure 3), t and the Barn kelp forest (BARN, Figure 4). The Units 1, 2, and 3 intakes (eircles), the Unit 1 outfall (triangle), and the Units 2 and 3 diffusers (labeled lines) are t shown.

I U.S. Geological Survey Map

Digitized using Summagraphics tablet and Sigmascan I software by Jandel Scientific on an IBM PC compatible Data transferred to IBM 4341 using CXI card

I COASTLNz DATA I ANNOMAPSAS DBANNO.S}IADE}'IAP I MAPPLOT SAS t Figure 1. I I I I I I I I 277 I I

I Figure 2. San Onofre kelp forest. The area of hard substrate is outlined in the upper figure, and the depth contours (m) are shown in the lower figure. The positions of various I sampling stations are also shown.

I PLOT 1: SOKmap with substrate profile

SOKSUBDATA I SOKNSUBDATA t SOKPLOTSAS Figure 2a. I I PLOT 2: SOK map with depth profiles Ecosystems depth profile maps

I Digiti-zed using Summagraphics tablet and Sigmascan software by Jandel Scientific on an IBM PC compatible I Data transferred to IBM 4341 using CXI card SOKIIA DATA SOKllB DATA SOK12 DATA SOK13A DATA SOK13B DATA I S0Kt4 DATA to S0K16 DATA I ANNODEPSAS DBANNO.SOKDEPTH I SOKZPLTSAS I Figure 2b. I I I t 278 I I

I Figure 3. San Mateo kelp forest. The area of hard substrate is outlined in the upper figure, and the depth contours (m) are shown in the lower figure. The positions of various I sampling stations are also shown. t I PLOT 1: SMKmap with substrate profile

SMK1SUBDATA I SMK2SUBDATA SMKPLOTSAS

I Figure 3a. I I PLOT 2: SMKmap with depth profiles SMK5 DATA tO SMK9 DATA SMK1OADATA to SMK14A DATA I SMKIOB DATA TO SMKl4B DATA SMK15 DATA to SMK18 DATA I ANNODEP2SAS DBANNO.SMKDEPTH I SMKZPLTSAS I Figure 3b. I I I I I 279 t I

I Figure 4. Barn kelp forest. The area of hard substrate is outlined in the upper figure, and the depth contours (rn) are shown in the lower figure. The positions of various sampling stations I are also shown.

PLOT 1: Barn kelp bed map with substrate profile I showing KIP station

I Ecosystems substrate profile maPs Digitized using Summagraphics tablet and Sigmascan I software by Jandel Scientific on an IBM PC compatible Data transferred to IBM 4341 using CXI card

O1BKSUBDATA to O2BKSUBDATA I O3BKSUBDATA to 1SBKSUB DATA 19ABKSUB DATA IgBBKSUB DATA I 20BKSUB DATA to 3sBKSUB DATA ANNOSUBBSAS

I DBANNO.BKSUB I BKPLOT SAS Figure 4a.

I PLOT 2: Barn kelp bed map with depth profiles t Ecosystems depth profile maps Digitized using Summagraphics tablet and Sigmascan I software by Jandel Scientific on an IBM PC compatible Data transferred to IBM 4341 using CXI card I BKTL DATA to BKI3L DATA BK14AL DATA BK14BL DATA BK15L DATA I BK16L DATA I ANNODEPBSAS DBANNO.BKDEPTH I BKZPLT SAS I Figure 4b. 280 I Figure 5. Sampling station for study of

Figure drawn by Leilani Bost. I

I Figure 6. San Onofre and San Mateo kelp forests. Benthic survey stations, kelp recruitment survey stations, and I physicaLlchemical survey stations are shown. I PLOT 1: SOK map Ecosystems substrate profile maps

I Digitized using Summagraphics tablet and Sigmascan software by Jande1 Scientific on an IBM PC compatible I Data transferred to IBM 4341 using CXI card SOKSUBDATA I SOKNSUBDATA ANNOSUBSAS I DBANNO.SOKSUB DBANNO.SOKNSUB I SOKPLT2 SAS t Figure 5a. I PLOT 2: SMK map Ecosystems substrate profile maps I Digitized using Summagraphics tablet and Sigmascan software by Jandel Scientific on an IBM PC compatible t Data transferred to IBM 4341 using CXI card SMKSUBDATA I SMKNSUBDATA ANNOSUBSAS

DBANNO.SMKSUB I DBANNO.SMKDSUB I SMKPLT2 SAS Figure 6b. I I 282 I I

I Figure 7. Schematic drawing of stations. used to sample kelp and sea urchin recruitment. A. September 1981 to December 1983. I B. May 1984 to November 1986. t Figures drawn by Leilani Bost. I Figure 8. Operating characteristics of the San Onofre Nuclear I Generating Station's Units l, 2, and 3 combined.

I DBSONGS.YRT6to DBSONGS.YRST SONGSPLTSAS I Figure 8. I

Figure 9. Operating characteristics of the San Onofre Nuclear I Generating Station's Units 2 and 3 combined.

I DBSONGS.YRSOtO DBSONGS.YRST I SONGSPLTSAS Figure 9. I I I I I I 283 I I

I Figures- 10- 13. Changes in density (number I ^2 ) in two classes of fixed 1-rn2 quadrats at sMK in the san Mateo kelp forest for several species of invertebrates. Qugdrats-. I were divided into th-ose through which an urchin "front" moved and those beyond the le-ding edge of the "front" which were unaffected. The moving aggregation of red urchins, strongylocentrotus franciscanus,- was first I observed @ects in September 1986. The vertical line dividei the data into "Before" and "After" I periods. I DBBENT.SURO2- DBBENT.SUR22

I I I BENTMEANSAS BENTMN2SAS BENTMN3SAS DBBENTMN.SURVO222 DBBENTM2.SURVO222 DBBENTM3.SURVO222 I I I I IMPCTPT3 SAS Figures 10- 13. I Figure 14. Changes in substrate comPosition in two classes of fixed 1-m2 quadrats at SOKUin the upcoast portion of the San I Onofre kelp forest. Quadrats were divided into those which had at leait 25% cover of silt on one or more surveys and those which always had less. A heavy deposit of silt was first noted in October 1985. The vertical line divides I the data into "Before" and "After" Periods. I DBBENT.SURO2 DBBENT.SUR22 I

I I I I BENTMEANSAS BENTMNzSAS BENTMN3SAS t DBBENTMN.SURVO222 DBBENTM2.SURVO222 DBBENTM3.SURVO222

I IMPCTPT3 SAS I Table L4. I 284 I I

I Figures I5-I7. Changes in density (number I ^2) in two classes of fixed 1-m2 quadrats at SOKUin the uPcoast portion of the San Onofre kelp forest for several species of I invertebrates. Quadrats were divided into those which had at least 25% cover on one or more surveys and those which always had less. A heavy deposit of silt was first noted in October 1985. The vertical line divides the t data into "Before" and "After" periods. I I DBBENT.SURO2- DBBENT.SUR22

I I I BENTMEANSAS BENTMN2SAS BENTMN3SAS I DBBENTMN.SURVO222 DBBENTM2.SURVO222 DBBENTM3. SURVO222 I IMPCTPT3 SAS Tables 15-17. I I I t I I T I I 285 I I

I Figures 18-19. Average percent cover (Fie. 18) or depth (Fie. 19) of silt in five randomly placed 1-m2 quadrats at stations used for the study of kelp recruitment. Stations are indicated by closed circles. Percent cover or depth of I silt was zeto unless otherwise indicated. t t. EcoSystems substrate profile maps

Digitized using Summagraphics tablet and Sigmascan I software by Jandel Scientific on an IBM PC compatible I Data transferred to IBM 434L using CXI interface SOKSUBDATA SOKNSUBDATA

I ANNOSUBSAS

DBANNO.SOKSUB I DBANNO.SOKNSUB 2. DBANNO.SOKSUB DBANNO.SOKNSUB I DBI.,IACCNT.SUROS DBMACCNT.SURO9 I DBCOORD.STATION OOZPLTSSAS I Tables 18 and L9. I I I T I I I 286 I I

I Figure- 20. Mean percent cover of sand + silt at stations in the San OnofrL, San Mateo, and Barn kelp forests. During the operational period, large quantities of silt covered many quadrats at the San Onofre stations, and a dense aggregation I of grazing red urchins moved through many of the quadrats at the San Mateo station. Data from affected and unaffected I quadrats were combined to calculate the station means. I DBBENT.SUROz - DBBENT.SUR22 BENTMEANSAS I DBBENTMN.SURVO222 BENTMNPLTSAS I I Figure 20. I I I I I I I I I I I 287 I t

I Figures 2L, 25, 29, 33, 37, 41, 45, 49, 53, 57, 61, 65, 69, 73, 77, 79, 83, and 87. Mean density of selected species at stations in the San Onofre, San Mateo, and Barn kelp forests. During the operational period, large quantities I of silt covered many quadrats at the San Onofre stations, and a dense aggregation of grazing red urchins moved through many of the quadrats at the San Mateo station. I Data from affected and unaffected quadrats were combined to calculate the station means. I DBBENT.SURO2 - DBBENT.SUR22 I BENTMEANSAS DBBENTMN.SURVO222 , I BFNTMNPLTSAS I

Figures 22,26,30, 34.-38, 42,45.-50, 54,58, 62,66,70, 74r 78, t 80, 84, and 88. Average deltas during the preoperational and operational periods for selected species. Deltas are the difference between the average density at the impact I and control sites. The horizontal lines are mean deltas for the before and after periods. The transformation used in the analysis is printed in the upper right-hand corner of each graph. During the operational period, large quantities I of silt covered many quadrats at the San Onofre stations, and a dense aggregation of grazing red urchins moved through many of the quadrats at the San Mateo station. Data from t affected and unaffected quadrats were combined to calculate the deltas. I DBBENT.SURO2 - DBBENT.SUR22 t BENTMEANSAS DBBENTMN.SURVO222

T BDLTPLT SAS I I I 288 t I

I Figures 23, 27, 31, 35, 39, 43, 47, 51, .55, 59, 63, 67, 7L, 75, 81, 85, and 89. Mean density of selected species at stations in the San Onofre, San Mateo, and Barn kelp forests. During the operational period, large quantities I of silt covered many quadrats at the San Onofre stations, and a dense aggregation of grazing red urchins moved through many of the quadrats at the San Mateo station. I Data from quadrats which had 25% or more silt on any survey, or which were affected by the urchin front, were I not used to calculate station means for any survey. t DBBENT.SURO2- DBBENT.SUR22 BENTMN2SAS I DBBENTMz.SURVO222 BENTM2PLTSAS I I

I Figures 24, 28, 32.- 36, 40, 44, 48, 52, 56, 60, 64, 58, 72, 76, 82, 86, and 90. Average deltas during the preoperational and operational periods for selected species. Deltas are I the difference between the average density at the impact and control sites. The horizontal lines are mean deltas for the before and after periods. The transformation used in the analysis is printed in the upper right-hand corner of I each graph. During the operational period, large quantities of silt covered many quadrats at the San Onofre stations, and.a dense aggregation of grazing red urchins moved through I many of the quadrats at the San Mateo stati-on. Data from quadrats which ]i.ad 25% or more silt on any survey, or which were affected by the urchin front, were not used to calculate I deltas for any survey.

I DBBENT.SUROz - DBBENT.SUR22 BENTMN2SAS

I DBBENTMz. SURVO222 I BDLTPLT2 SAS I I 289 I