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Genetic variation in three North American barn owl (Tyto alba) populations using DNA fingerprinting McLarty, Joanne Ruth 1995

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GENETIC VARIATION IN THREE NORTH AMERICAN BARN OWL (Tyto alba) POPULATIONS USING DNA FINGERPRINTING by JOANNE RUTH McLARTY B.Sc, The University of British Columbia, 1992 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES Department of Animal Science We accept this thesis as conforming to the reauired standard THE UNIVERSITY OF BRITISH COLUMBIA August 1995 ® Joanne Ruth McLarty, 1995 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department The University of British Columbia Vancouver, Canada DE-6 (2/88) 11 A B S T R A C T I studied the genetic diversity of a small population of common barn owls (Tyto alba) in British Columbia (BC), Canada. DNA fingerprinting was employed to assess the level of genetic variation in the BC population compared to two other barn owl populations in North America, California and Utah. Two different multilocus probes, Jeffreys' 33.15 and per, were used with the restriction enzyme Haelll. These probes yielded sufficient variation at minisatellite loci to assess the general level of relatedness both within and between populations. The number of scorable bands on each fingerprint was significantly higher when probed with per than when probed with Jeffreys' 33.15, but both probes resulted in similar band sharing patterns, and neither showed any apparent linkage. Band sharing between each pair of individuals on a gel was calculated as In^Kjif^ + nB),' where n A and wB are the number of bands in the fingerprints of individuals A and B, and n A B is the number of bands shared by A and B. Band sharing coefficients were significantly higher in the BC barn owl population than in the California or the Utah populations, indicating less genetic variation in the BC population compared to the other two. Between population band sharing was highest between Utah and California, reflecting more genetic similarity between those two populations. The results indicated that the genetic variation in the BC population is still within the range of other viable populations. Levels of organochlorine and PCB residues in barn owl livers also have dropped consistently since 1975 (Appendix 1). To conserve Canada's barn owls, it will be important to continue monitoring genetic variation in the BC population and to maintain barn owl habitat in the Fraser Valley. I l l TABLE OF CONTENTS Page ABSTRACT ii LIST OF TABLES v LIST OF FIGURES vi ACKNOWLEDGEMENTS vii 1. INTRODUCTION 1 2. STUDY SITES 5 3. METHODS 3.1 Location and Handling of Birds 7 3.2 Blood Sample Collection 9 3.3 DNA Fingerprinting 3.3.1 DNA Extraction 9 3.3.2 DNA Quality Assessment and Quantitation 10 3.3.3 Southern Blotting and Hybridization 10 3.4 Scoring and Analysis of Fingerprints 13 4. RESULTS 4.1 DNA Fingerprint Patterns 15 4.2 Probe Differences 19 4.3 Band Sharing Within Populations 19 4.4 Band Sharing Between Populations 23 iv 4.5 Within Nest Comparisons 23 5. DISCUSSION 5.1 DNA Fingerprinting Methods 26 5.2 Genetic Variation in Barn Owl Populations 31 5.3 Conclusions 36 6. REFERENCES 38 7. APPENDDII 45 8. APPENDIX II 51 V LIST OF TABLES Table Page 1. Fingerprint layout. 15 2. Mean number of bands per fingerprint lane. 21 3. Mean'band sharing among siblings within populations. 22 4. Mean band sharing among unrelated individuals within populations. 22 5. Mean band sharing between populations. 22 6. Mean band sharing within and between two clutches from the same nest site. 27 A - l . Organochlorine and PCB residues in BC barn owl livers, 1994. 48 vi LIST O F F I G U R E S Figure Page 1. Map of British Columbia study area. 6 2. Map of western North America showing location of three study sites. 8 3. DNA fingerprint of barn owls from three populations using Jeffreys' 33.15 probe. 17 4. DNA fingerprint of barn owls from three populations using per probe. 18 5. DNA fingerprint of X-bacteriophage probed DNA. 20 6a. Band sharing among BC barn owls using Jeffreys' 33.15 probe. 24 6b. Band sharing among Utah barn owls using Jeffreys' 33.15 probe. 24 6c. Band sharing among California barn owls using Jeffreys' 33.15 probe. 24 7a. Band sharing among BC barn owls using per probe. 25 7b. Band sharing among Utah barn owls using per probe. 25 7c. Band sharing among California barn owls using per probe. 25 8a. Band sharing frequency distribution of two consecutive clutches from the same nest using Jeffreys' 33.15 probe. 28 8b. Band sharing frequency distribution of two consecutive clutches from the same nest using per probe. 28 A - l . Organochlorine and PCB residues in BC barn owl livers. 49 Vll A C K N O W L E D G E M E N T S I wish to express my appreciation to those people who have aided in this study. I would like to thank my supervisor, Dr. Kimberly Cheng for his time and advice in the design and writing of the thesis and Dr. John Eadie for the use of his DNA fingerprinting laboratory and the invaluable assistance he provided me while in Toronto. Thanks to my committee members, Drs. Jamie Smith, George Iwama, and John Eadie who have provided advice and criticisms on the thesis. A special thanks to Dick Cannings for his valuable inputs, and Dr. Martin Adamson, who was of great assistance to me in a related study on barn owl parasites. I wish to thank Dr. Carl Marti of Weber State University for the collection of blood samples from barn owls in Utah and his inputs during the preparation of this thesis, and Dr. Peter Bloom of the Western Foundation of Vertebrate Zoology for collecting blood samples in California. The DNA fingerprinting theory and methods would have been much more difficult to master if not for the assistance and knowledge of David Anstey, Dr. Wes Hochachka, Raniero Fernando and Graeme Gissing of the University of Toronto, Scarborough Campus, and Dr. Dan Heath of the University of British Columbia. The field work in BC would not have been possible without the extensive survey and field assistance from Lorraine Andrusiak, to whom I am deeply indebted. Special thanks also go to John Elliott, Laurie Wilson, and Henry T. Won of the Canadian Wildlife Service; Monika Tolksdorf and volunteers at Monika's Wildlife Shelter; Colleen Stranix and the staff and volunteers at the OWL Rehabilitation Centre; Adele Stapleton and the Friends of Boundary Bay; Mike Mackintosh and the volunteers from the Stanley Park Zoological Society; Mike Chutter and Tom Plath of the BC Ministry of the Environment; and the property owners in the Lower Mainland area who allowed me onto their property and into their barns. I also thank the Natural Sciences and Engineering Research Council of Canada (NSERCC), the University of British Columbia, the C.W. Roberts Jr. Memorial Scholarship Fund and the Gillmor and Roderick Morrison Memorial Fund for financial assistance during this study. Finally, for all their support and assistance, I thank my parents, Don and Ruth, my brother, Stephen, my boyfriend, Jaime Doyle, and his family, Aimie, Mrs. and Mr. Doyle. 1 1. INTRODUCTION Though the barn owl (Tyto alba) is one of the most widely distributed birds in the world (Prestt and Wagstaffe 1984), its populations are declining due to habitat loss in many regions, particularly England, many other parts of Europe (Bunn et al. 1982, Shawyer 1987, Taylor 1994) and in the upper midwestern United States and Canada (Stewart 1980, Campbell and Campbell 1983, Colvin 1985, Marti 1987, Marti 1992). In Canada, barn owls have been classified as "vulnerable" by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) (Munroe 1991). The only population is presently located in the southwestern corner of British Columbia (BC) (Campbell and Campbell 1983). A small population was previously recorded in southern Ontario (Campbell and Campbell 1983), but it has since been extirpated (Kay McKeever, pers. comm.). The BC population of approximately 1000 individuals (Campbell and Campbell 1983) is located in the Lower Mainland, adjacent to the city of Vancouver, and on southern Vancouver Island. This non-migratory population (Andrusiak and Cheng, in press) is at risk of extinction as Greater Vancouver spreads out into the Fraser Valley, turning prime barn owl habitat, open fields and agricultural areas, into golf courses and suburban housing developments (Moore 1990). Most research on BC barn owls has concentrated on food habits (Cowan 1942, Dawe et al. 1978, Campbell et al. 1987), while recent studies have examined reproductive and mortality patterns as well as habitat use and preference (Andrusiak 1994, T. Sullivan unpubl. data). Unpublished observations by Terry Sullivan suggest that breeding pairs are limited by foraging habitat. It is hypothesized that established 2 pairs in habitat that supports a healthy population of voles (Microtus townsendii) are able to breed year after year, while younger individuals in the population must depend on marginal habitat that has a smaller vole population. In poor vole years, the marginal habitat is insufficient to support the production of young, hence only those pairs with good habitat and steady vole numbers can breed. The resulting population may be made up of a large number of offspring from a few pairs plus a few offspring from other pairs. Taylor (1994) has also observed this pattern on his study site in Scotland. Dispersal in the BC barn owl population occurs within 20-km of the nest and in a predominantly eastward direction (Andrusiak 1994). Unfortunately, as one moves eastward, the amount of barn owl habitat decreases and each owl requires a larger foraging area (Andrusiak 1994). A study of band and mortality records from the BC Ministry of the Environment indicated very little movement of barn owls from Washington State to BC or vice versa (Andrusiak, pers. comm.). Therefore, as suitable habitat decreases further and becomes fragmented due to urbanization, a subsequent decrease in available prey and reduced numbers of breeding owls may result. Eventually, a limited gene pool for BC barn owls could cause genetic problems for the population, as the same small number of pairs produce most of the young for the next generation. Successful conservation requires a healthy population size and a minimum gene pool in addition to a healthy habitat in order for a species to survive. Despite the large amount of research that has been conducted on barn owls world wide, there have been few studies of population genetics. Population studies consist of radio-telemetry (Taylor 1994), recapturing banded birds (Marti 1994, Taylor 1994), recovering dead birds that 3 have been banded (Marti and Wagner 1985, Andrusiak 1994) and a minimal amount of protein electrophoresis (Randi et al. 1991). Direct observation of barn owls is difficult because they are nocturnal and capturing adult barn owls is time consuming and yields varying results (Andrusiak 1994, Taylor 1994, Sullivan pers. comm.). While banding adult owls and nestlings enables researchers to monitor individuals in a population (Andrusiak 1994, Marti 1994, Taylor 1994), it is difficult to recapture banded birds and bands are rarely recovered from dead individuals. Monitoring the population in this way allows a look at dispersal patterns in the population, but it is often difficult to assess the actual relatedness of individuals. A more direct look at the genetic makeup of individuals is useful for conservation purposes. Methods such as protein electrophoresis (Randi et al. 1991), mitochondrial DNA analysis (Mulligan et al. 1992), ribosomal DNA analysis (Davis et al. 1990), and DNA fingerprinting (Lehman et al. 1992) allow a thorough examination of the genetic structure of populations. The first three of these methods often require sacrificing the animal, hardly a desirable choice when one is concerned with the conservation of a population. DNA fingerprinting, on the other hand, requires only a small blood sample that yields enough DNA for several analyses. Since its initial development by Jeffreys et al. (1985a, 19856), DNA fingerprinting has become a valuable tool used in behavioural ecology and other fields of biology. DNA fingerprinting detects hypervariable minisatellites throughout the genome. Minisatellites are sequences of DNA that are made up of multiple tandem repeats of short 10-70 base-pair units which are widely scattered throughout the 4 chromosomes of many species (Austin et al. 1993, Blanchetot and Gooding 1993). Hypervariability at individual minisatellite loci is the result of differences in the number of tandem repeats (Austin et al. 1993). Probes made of repeats of the core sequence can be used to detect hypervariable minisatellites at multiple loci (Jeffreys et al. 1985a, Shin et al. 1985, Vassart et al. 1987, Longmire et al. 1990, Austin et al. 1993). A number of probes are commonly used for DNA fingerprinting, each of which hybridizes to a different subset of minisatellites (Jeffreys et al. 1985a, Shin et al. 1985, Vassart et al. 1987, Longmire et al. 1990, Harris et al. 1991). DNA fingerprints are therefore useful in assessing genetic differences at a large number of DNA sites across the genome of a population (Jeffreys 1987, Grunder et al. 1994). The result is a pattern of bands on a radiogram that is unique to each individual, is inherited in a Mendelian fashion, and shows high somatic and germ line stability (Jeffreys et al. 19856, Bruford et al. 1992). Though they have been primarily used to assess parentage (Westneat 1990, Harris et al. 1991, Graves et al. 1992, Longmire et al. 1992), multilocus probes have more recently been used to analyze differences within and between populations (Gilbert et al. 1990, Reeve et al. 1990, Bruford et al. 1992, Lehman et al. 1992, Triggs et al. 1992, Zeh etal. 1992, Blanchetot and Gooding 1993, Timms etal. 1993, Grunder etal. 1994, Rave 1995). The genetic similarity of populations and the degree of inbreeding within populations can be reflected in banding patterns found in DNA fingerprints (Grunder et al. 1994). Although this method cannot be used to predict exact genealogical relationships among individuals (Lynch 1988), it allows determination of the general relatedness of individuals in a population, with DNA fingerprints becoming more similar 5 the closer related individuals are (Cumrriings and Hallett 1991, Mannen et al. 1993). The BC barn owl population was my primary interest, but to interpret the genetic variation in this population, I compared it to two other barn owl populations. Utah represents an area where dispersal and recruitment of barn owls can occur from various directions, while California is restricted on the west side because of the Pacific Ocean. In BC, recruitment can only occur from the south, though it is infrequent (Andrusiak pers. comm.). These three regions are close enough, however, that there should be some genetic similarity, allowing for a direct comparisons of DNA fingerprints of the populations. My objectives were to: (1) generate multilocus DNA fingerprints for the three barn owl populations using the minisatellite probes Jeffreys' 33.15 and per, and (2) use the fingerprints to examine the genetic similarity within and between barn owl populations in California, Utah, and British Columbia. Additionally, a small study on organochlorine and PCB residues in barn owl livers was conducted and is reported in Appendix I. 2. S T U D Y S I T E S The main study population was located in the southwestern corner of British Columbia, in the Lower Fraser Valley (Figure 1). Barn owls in this area are associated mainly with agricultural areas, though they are also seen in more urban regions. The study area covers approximately 300,000 hectares (Moore 1990); the distance between 6 Figure 1. Map of British Columbia study area showing barn owl breeding range (dashed border) and nest sites (•) (n=27). Map redrawn from Andrusiak 1994. 7 nest sites (n=27) varied from 0.5 km to 80 km. Blood samples from barn owls were also collected in Utah and California (Figure 2). Samples were collected with the assistance of Dr. Carl D. Marti of Weber State University in Box Elder County and Davis County, Utah at nest sites (n = 18) ranging from 0.5 to 65 km apart. Barn owls in this area breed almost exclusively in human-made structures and are associated with irrigated agriculture (Marti 1994). Peter H. Bloom of the Western Foundation of Vertebrate Zoology assisted in collecting barn owl blood samples in Orange County, California at nest sites (n=10) within 5 km. 3. METHODS 3.1 Locating and Handling of Birds The location of nest sites was previously determined (Andrusiak 1994), while an ongoing nestbox program (Blood and Dueck 1992, Andrusiak et al. 1993) provided additional sites for nesting. Nest sites were monitored from May through November 1993. Initial visits early in the season were made to note any nesting attempts and to determine the time when the nest should be next visited. Most nestlings were bled and banded at 4 to 8 weeks of age. Some females captured in nest boxes were also bled and banded. Nestlings were removed from the nest and lowered in a plastic bucket to the ground. Each nestiing was kept in a separate container on the ground to prevent sibling aggression. In addition to blood samples being taken from each individual for DNA analysis (see below), standard measurements (wing chord, tarsus length, tarsus width, Figure 2. Map of western North America showing location of three study sites; A=British Columbia site, B=Utah site, and C=California site. 9 talon length and beak length and weight) were taken for a concurrent study. Birds were banded with Canadian Wildlife Service numbered aluminum leg bands before being returned to the nest. 3.2 Blood Sample Collection Blood samples of approximately 50 ul were collected from the brachial vein of each barn owl. The vein was punctured with a 23-gauge needle and blood was collected in a heparinized capillary tube. After collection, the blood was immediately transferred to microcentrifuge tubes containing 1.0 ml Queen's lysis buffer (Seutin et al. 1991) for storage. Samples were kept at ambient temperature for no more than 12 hours in the field before being refrigerated at 4 °C until the DNA could be extracted and processed. 3.3 DNA Fingerprinting 3.3.1 DNA Extraction The extraction protocol developed by Seutin et al. (1991) was used. Only half of each sample was extracted, ensuring that enough blood would remain for future analysis and as backup in case of any errors. This sample was brought up to 4 ml with Applied Biosystems lysis buffer and incubated in a 37 °C shaking water bath until the cells were completely lysed and the content uniformly mixed (5 hours to overnight). The samples were then further incubated at 37 °C with 400 /xl of proteinase K (Boehringer Mannheim; 20 units/mg) for approximately 8 hours or until the samples turned a uniform green colour. DNA was purified by one phenol:chloroform:isoamyl alcohol (25:24:1) extraction and one chloroform:isoamyl alcohol (24:1) extraction, then precipitated by the addition of 0.1 volume of 3 M sodium acetate and 2.0 volumes of -20 °C 95% ethanol. DNA was collected on a glass pipette, rinsed in 70% ethanol, air dried, and resuspended in 300 p\ of TE, pH=7.6 (10 mM Tris, 1 mM EDTA). 3.3.2 DNA Quality Assessment and Quantitation DNA quality was assessed via gel electrophoresis of undigested DNA. Whole DNA was run in a 0.8% agarose gel and visualized via ethidium bromide staining. Any degradation or other deviations from normal were noted. Samples were assumed to average approximately 0.25 ng/fd of DNA, with this concentration adjusted by comparisons of intensity among the staining of undigested samples. Approximately 2 ul of each sample was then cut with the restriction enzyme EcoRl (New England BioLabs) and electrophoresed on a 0.8% agarose gel along with precut barn owl standards of known concentrations. This standard was created by comparing it to a human standard of known concentration. The concentration of each sample was estimated by comparison to the standard and then electrophoresed again to confirm or further adjust the estimate. This enabled a fairly accurate quantitation of the DNA samples which in turn contributed to even loading of the gels. 3.3.3 Southern Blotting and Hybridization Approximately 10 /ig of each DNA sample was digested with 50 units of Haelll 11 using the reaction buffer provided by the supplier (New England BioLabs). After 5 hours of incubation at 37 °C, 50 additional units of HaeUI were added and the incubation was allowed to continue overnight. Complete digestion of the DNA and confirmation of the concentration were assessed by running 0.5 fig of the sample on a 0.8% agarose gel. Any adjustment in concentration was done before the samples were ethanol precipitated and resuspended in TE, pH=7.6 to a final concentration of 0.5 fig/fd DNA. Samples that were not fully digested were subject to a final 50 units of HaeUI for 5 hours before being precipitated and resuspended. Three fig of each DNA sample were electrophoresed on a 1% agarose gel to separate the fragments. Prior to loading, 5.0 fil of loading buffer (0.25% bromophenol blue, 15% Ficoll, 0.05 M EDTA) and 0.05 fig of Hindlll/EcoRl digested lambda DNA were added to each sample. The lambda DNA served as a molecular weight standard that acted as a control between lanes on a gel. In the outer two lanes of each gel, barn owl standard was run as a measure of control between gels. Electrophoresis was carried out on 20 cm long gels at 30 volts for 42 hours in a lxTBE (0.09 M Tris-borate, 0.002 M EDTA) running buffer. The buffer was constantly recirculated and changed completely after 20 hours. After 42 hours, each gel was stained in 2 fig/ml ethidium bromide and the DNA visualized with a 300 nm transilluminator. Bands from the lambda DNA were clearly visible amongst the smear of genomic DNA and were measured manually with a ruler from the wells of the gel in case of problems with the lambda hybridizations. The gel was then depurinated in 0.25 M HC1 for 15 minutes, denatured in 0.4 M NaOH and 1.5 12 M NaCl for 75 minutes, and neutralized in 0.5 M Tris-HCl, pH=7.5 and 1.5 M NaCl for 60 minutes. DNA was transferred to Immobilon-N membrane (Millipore) via Southern blotting in lOxSSC (1.5 M NaCl, 0.15 M Na-citrate) for at least 16 hours (Southern 1975). After transfer, the membrane was air-dried at room temperature for 2 hours, followed by baking at 80 °C for 2 hours to fix the DNA on the membrane. Prior to hybridization, small dots of IBI Glo-Juice were placed in the corners of each blot to allow for easy alignment of the autoradiographs. Glo-Juice emits light after exposure to a light source, which in turn shows up as an exposed area on the x-ray film. Membranes were prehybridized in 15-ml of hybridization solution (7% SDS, 1 mM EDTA[pH=8], 0.263 M Na2HP04, 1% BSA) (Westneat et al. 1988) for 3 hours at 65 °C in a hybridization oven. Two probes were used on each membrane, Jeffreys' 33.15 probe (Jeffreys et al. 1985a) and the per probe (Shin et al. 1985), in addition to bacteriophage lambda DNA which enabled visualization of the molecular weight standards. These two minisatellite probes were chosen because they were readily available and preliminary testing proved their use in analyzing barn owl DNA. Two entirely different probes were used to ensure that each probe was giving an accurate assessment of variation and to account for any cases of linkage. Probes were labelled with [a-32P]dCTP using an oligolabelling kit (Pharmacia), with unincorporated nucleotides removed via a Sephadex G-50 nick column (Pharmacia). Membranes were hybridized with 32P-dCTP randomly labelled probe for 16-24 hours. After hybridization, membranes were washed twice in 2xSSC, 0.1 % SDS at room temperature for 15 minutes 13 each followed by two 65 °C washes with 2xSSC, 0.1 % SDS, the first for 15 minutes and the second for 30 minutes. Each membrane was rinsed in lxSSC prior to being wrapped in plastic wrap and set up for autoradiography. Membranes were exposed to x-ray film (Kodak XAR) between two Kodak intensifying screens for 24 hours at -70 °C. This allowed a preliminary view of the fingerprint and an estimate of the exposure time required without intensifying screens. Each membrane was then exposed to x-ray film at -70 °C without intensifying screens for the appropriate amount of time (4 to 10 days). After the production of an acceptable autoradiograph, membranes were stripped with a solution of boiling O.lxSSC, 0.1% SDS, 1 mM EDTA in a series of three 10 minute washes at 85 °C. The membranes were then exposed to a diagonally placed strip of x-ray film for up to one week to check for complete stripping. Stripped membranes were then available to be rehybridized with a different probe. 3.4 Scoring and Analysis of Fingerprints DNA fingerprints were scored by naked eye using a light box (Austin et al. 1993, Lifjeld et al. 1993). Lambda blots for each autoradiograph were first copied onto acetate sheets using an overhead pen to mark each band and the reference points of the gel. Next, the same procedure was followed for each of per and Jeffreys' 33.15 blots, using a different colour pen for each probe. Finally, the autoradiograph for one probe, its corresponding acetate sheet, and the acetate copy of the lambda blot for that gel were overlaid on the light box. Using the lambda markers as reference, each band was marked as present or absent in each lane of the gel using a grid like matrix. Bands were 14 scored as representing the same allele if they appeared to have the same relative intensity and differed in migration distance by less than 0.5 mm, hence having similar molecular weights, as determined from the lambda markers. There was no attempt to assign molecular weights to the bands of individual fingerprints. Scoring only took place between 2 and 20 kb, as bands outside of this area tended to be fuzzy. Any lanes that showed fewer than five bands were not included in the analysis as it was assumed that not all of the bands were visible at that particular intensity and therefore the pattern was not representative of the individual. A total of nine fingerprint gels were run. Fingerprints consisted of 18 lanes of samples and two lanes of barn owl standard. Table 1 shows the population layout of each fingerprint. Band sharing or fingerprint similarity, the proportion of bands shared between each pair of individuals on a gel, was calculated as In^l(nA + nB), where nA and nB are the number of bands in the fingerprints of individuals A and B, and nAB is the number of bands shared by A and B (Wetton et al. 1987). Band sharing was calculated for siblings and unrelated individuals within each population as well as between individuals from different populations. Band sharing among siblings gave a measurement of variation among individuals with a known relationship, a relationship that was consistent for comparison of all three populations. Band sharing estimates among unrelated individuals were calculated between individuals of unknown relationship. Band sharing was calculated only between individuals on the same gel. Mean band sharing values were calculated combining the data from each gel. Mantel tests (NTSYS-pc; Rohlf 1994) were used to determine differences in band 15 Table 1. Fingerprint Layout. Fingerprint Samples 1 BC Siblings 2 BC Siblings 3 Utah Siblings 4 BC Unrelated 5 Utah Unrelated 6 BC and Utah Unrelated 7 BC and Utah Unrelated 8 California Siblings 9 BC, Utah, and California Unrelated * Fingerprints with samples from more than one population have samples from each population alternating lanes. * In all three populations, unrelated individuals were taken from different sibling groups. For BC and Utah, a few additional birds not used in sibling comparisons were also included to increase the sample size. 16 sharing (Rave 1995) among the three barn owl populations. Two matrices consisting of band sharing coefficients between pairwise combinations of birds and their corresponding population were compared using the Mantel test statistic Z (NTSYS-pc; Rohlf 1994, Rave 1995). Significance among band sharing was determined by comparing r-values which were calculated from Z-values with the standard f-distribution (Schnell et al. 1985) and by comparing Z-values with 250 random samples of their permutational distributions (Rohlf 1994, Rave 1995). Two-tailed Mests were used to compare the number of bands per fingerprint lane. 4. RESULTS 4.1 DNA Fingerprint Patterns The minisatellite probes Jeffreys' 33.15 and per both detected many polymorphic fragments in //aelll-digested barn owl DNA. These fragments varied considerably both within and between the three populations (e.g. see Figures 3 & 4). The two gels represent the same fingerprint (BO-10-94) probed with the two probes and contain unrelated individuals from the BC population, the Utah population, and the California population. The fingerprints show considerable variation among individuals of the same population and among individuals of different populations. The DNA probed with per shows a fingerprint with some bands that are considerably darker than other bands while the bands on Jeffreys' 33.15 probed blots are more uniform in colour. This contrast may reflect differences in copy number. The outer lanes on either gel (lanes 1 and 20) are of the barn owl standard DNA 17 LANE 1 2 3 4 5 6 7 8 9 10 n 12 13 14 15 16 17 18 19 20 SAMPLE S C B U C B U C B U C B U C B U C B U S Figure 3. DNA fingerprint of barn owls from BC, Utah, and California using Jeffreys' 33.15 probe. This is the segment of the gel is the area that was scored. Samples: S=barn owl standard; C=California; B=BC; and U=Utah. 18 KB —21 LANE S A M P L E S C B U C B U C B U C B U C B U C B U S Figure 4. DNA fingerprint of barn owls from BC, Utah, and California using per probe. This is the segment of the gel is the area that was scored. Samples: S=barn owl standard; C=California; B=BC; and U=Utah. 19 that was cut with EcoRl; the banding pattern in the outer lanes is therefore the same. The standard was run on all gels and always showed the same pattern with the same probe, though the number of visible bands sometimes differed due to differences in the strength of the hybridization signal. Clear fragments were visible between 2 and 20 kb as determined by the molecular weight markers (Figure 5). Outside of this range, bands blended together, were difficult to distinguish, and therefore were not scored. 4.2 Probe Differences Slightly different results were found when using the Jeffreys' 33.15 and per probes. The mean number of scorable bands for each individual was higher when probed with per than when probed with Jeffreys' 33.15 in all cases (Table 2). This difference was significant (P< 0.025) in all populations except California. Band sharing calculations were generally higher with per than with Jeffreys' 33.15 (Tables 3, 4 & 5). 4.3 Band Sharing Within Populations Gels that contained sets of siblings and those with unrelated individuals from one population were used to assess the variation within each population, which in turn were compared to determine population differences. There were no significant differences in the number of bands scored in each of the populations using Jeffreys' 33.15 probe, but BC and Utah displayed significantly more bands than California when probed with per. Band sharing coefficients were calculated for siblings and for unrelated 2 0 Figure 5. D N A fingerprint of Hindlll/EcoRl cut X-bacteriophage D N A . This gel was used as a standard to align fingerprint gels and determine the appropriate area to score. 21 Table 2. Mean number of bands per fingerprint lane. BC Utah California mean±sd n mean±sd n mean±sd n 33.15 9.4+1.8a 58 10.0±2.3 a 25 9 .0±1.1 12 per 12.9+2.7 58 14.0+2.5 25 9 .1±2 .6 b 12 ' Significantly different (P< 0.025) from bands detected with per in same population. b Significantly different (P<0.05) from BC and Utah probed with per. 22 Table 3. Mean band sharing among siblings within populations. BC Siblings Utah Siblings California Siblings mean±sd n mean±sd n mean±sd n 33.15 0.67+0.16a 47 0.45±0.21" 10 0.48+0.19" 7 per 0.66+0.12a 47 0.50±0.20 b 11 0.46±0.20" 7 For each probe, means that were significantly different (P<0.01) are followed by a different letter. Note: "n" represents the number of band sharing coeffients that were used to get the mean. Table 4. Mean band sharing among unrelated individuals within populations. BC Unrelated Utah Unrelated California Unrelated mean±sd n mean±sd n mean±sd n 33.15 0.29+0.14" 152 0.24+0.12" 120 0.20+0.15" 27 per 0.31+0.12" 153 0.31+0.13" 119 0.23+0.15" 28 For each probe, means that were significantly different (P<0.01) are followed by a different letter. Note: 11 n" represents the number of band sharing coeffiecients that were used to get the mean. Table 5. Mean band sharing between populations. BC - Utah BC - California Utah - California mean±sd n mean±sd n mean±sd n 33.15 0.18±0.12 162 0.15±0.11 16 0.25±0.13 21 per 0.42±0.01 162 0.23±0.11 14 0.24±0.10 18 * No significant difference (P=0.01) between any same probe band sharing values. Note: "n" represents the number of band sharing coeffiecients that were used to get the mean. 23 individuals in each population. As expected, band sharing was significantly higher among siblings than among unrelated individuals in all populations with both probes. Frequency distributions of band sharing among siblings and unrelated individuals for each population using each probe are shown in Figures 6a-c and 7a-c. The distributions show up as two bell curves that overlap considerably in the middle area, though the smaller the sample size, the more skewed the curves are. Band sharing in the BC population was significantly higher (p<0.01) than both California and Utah with both probes except in the case of BC and Utah unrelated birds with the per probe (Tables 3 and 4). The significant difference was small for unrelated individuals and large for related birds. There was no significant difference found in band sharing between California and Utah except in the case of unrelated individuals with the per probe. 4.4 Band Sharing Between Populations Fingerprint gels with more than one population represented were used to assess the genetic relationships between the populations. When examining the band sharing coefficients between individuals of different populations, it was found that Utah and California had the highest band sharing between them, followed by BC and Utah, and finally BC and California (Table 5). 4.5 Within Nest Comparisons In one case, 2 successful clutches from the same nest were sampled in one year. These were run on the same gel to assess the degree of relatedness between them and 24 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Band sharing Figure 6a. Band sharing among BC barn owls using Jeffreys' 33.15 probe. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Band sharing Figure 6b. Band sharing among Utah barn owls using Jeffreys' 33.15 probe. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Band sharing Figure 6c. Band sharing among California barn owls using Jeffreys' 33.15 probe. 25 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Band shariig Figure 7a. Band sharing among BC barn owls using per probe. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Band sharing Figure 7b. Band sharing among Utah barn owls using per probe. Figure 7c. Band sharing among California barn owls using per probe. 26 determine if they were produced by the same parents. Within clutch band sharing and between clutch band sharing were very similar (Table 6). This suggests the two clutches are probably full siblings. Frequency distributions of within and between clutch band sharing are shown in Figures 8a and 8b. These distributions show considerable overlap in the within and between clutch band sharing, which lean towards the middle (33.15) or upper (per) range of band sharing as would be expected for full siblings. 5. DISCUSSION 5.1 DNA Fingerprinting Methods Jeffreys et al. (1986) demonstrated that two different DNA minisatellite probes, 33.15 and 33.6, detected different families of hypervariable loci, but that the general attributes of the DNA fingerprints (number of bands scored, band sharing, and levels of allelism and linkage) were similar with these two probes (Brock and White 1992). In this study, the two different probes gave the same trend in the population data, however the number of scorable bands and the band sharing values were slightly higher with per than with Jeffreys' 33.15. Differences in these DNA fingerprint attributes have also been seen in studies with other probes (Cummings and Hallett 1991). Jeffreys' 33.15 and 33.6 are human minisatellites (Jeffreys et al. 1985a). They are much more similar to one another than to probes from other sources (such as per which is isolated from Drosophila (Shin et al. 1985)) and may tend to yield more similar results even though they are detecting different DNA fragments. It is useful to employ more than one probe when analyzing DNA fingerprints because it allows an assessment of the probe. 27 Table 6. Mean band sharing within and between two clutches from the same nest site. BS Within Clutch BS Between Clutch 33.15 0.47+0.18* 0.52+0.06 per 0.70+0.11* /\i4-4-£±f£±*y+ / T ) ^f" (\ U r t + i i » / - v 0.72+0.08 *Not significantly different (P< 0.025) from between clutch band sharing. 28 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Band sharing Figure 8a. Band sharing frequency distribution of two consecutive clutches from the same nest using Jeffreys' 33.15 probe. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Band sharing Figure 8b. Band sharing frequency distribution of two consecutive clutches from the same nest using per probe. 29 Different probes should yield similar trends as is seen in this study, but comparing band sharing and other measures of similarity between different probes should not be done. The use of two different DNA fingerprint probes in this study also allowed for a measure of control between gels. The two probes gave similar patterns, thus confirming the results from the other probe. To further increase the number of scorable bands, different restriction enzymes and other probes, including single locus probes, could be utilized. The number of scorable bands detected on barn owl DNA fingerprints ranged from 6 to 17 using Jeffreys' 33.15 and from 6 to 20 using per (Table 1). These values are lower than those scored in a number of other studies using the same probes (Jeffreys and Morton 1987, Jones et al. 1991, Brock and White 1992, Hanotte et al. 1992, Triggs et al. 1992, Lifjeld et al. 1993). In many of these studies, bands were analyzed over a larger range or entire area of the gel (Jones et al. 1991, Brock and White 1992, Triggs et al. 1992, Lifjeld et al. 1993). In this study, bands were only analyzed between 2 kb and 20 kb, as bands outside of this range were fuzzy and indistinguishable. In this range, the number of bands scored were similar to that found by Reeve et al. (1990) who analyzed over a similar area of the gel. Only clearly distinct bands were counted in the analysis, while any faint or questionable bands were disregarded as it they would provide error rather than information to the data. In fact, some researchers have scored only a selected number of the most intense bands to reduce errors caused by misassigning fainter bands (Kuhnlein et al. 1990, Mannen et al. 1993). From the research done for this study, it is evident that one should not conduct 30 comparisons of individual fingerprints between separate gels. There were differences in the number of bands scored for the barn owl standard on different gels, yet it was apparent that the banding pattern was the same and the anomalies were due to differences in hybridization strength and exposure time, which in most cases can only be partially controlled by the researcher. Therefore, any direct comparison between individuals run on separate gels could create misleading results. DNA fingerprint analysis requires the assumption of no linkage disequilibrium (Brock and White 1991, Burke et al. 1991, Bruford et al. 1992). Generally, this requires a segregation analysis of a large pedigree consisting of two parents and > eight offspring (Bruford et al. 1992). Capture of both parents of a barn owl family can be difficult, especially locating the male and positively identifying his nest. Sexing of barn owls is also difficult, though breeding females do show a brood patch while the males do not (Taylor 1994). For these reasons, samples from both parents of barn owl broods were not available and therefore a pedigree analysis was not possible in this study. However, a pseudo-pedigree analysis was performed on the two families from the same nest. A few bands were always found together, but these bands did not occur together when other families on the same gel were examined. There are many bands that were never found together, but this does not necessarily imply linkage. Again, looking at other families on the same gel dismissed some of these cases, and other bands occur infrequently so that it is not unreasonable to find that they do not occur with some of the other bands. As well, no patterns of linkage were observed during manual scoring as have been seen in other species evaluated in the same laboratory (R. Fernando, pers. 31 comm.). This observation, in itself, has been proposed as a method of ruling out linkage (Amos et al. 1992). For this study, the determination of levels of relatedness depended on the comparisons of sibling and non-siblings. Although using only sibling and non-sibling measurements may seem restrictive, the design was necessary because I could not capture adult barn owls (D. Anstey, pers. comm.). Nestlings, on the other hand, are easy to capture and handle, in addition to having a known relationship. Nestlings found in the same brood were assumed to be full siblings and those from different nests assumed to be no more closely related than first cousins, based on what is known of barn owl breeding strategy (Marti 1992, Taylor 1994). If adults were used for the analysis, there would be no way to know the relationships among them. As well, comparisons between non-siblings were made between individuals from different parts of the range, further reducing the chance they were close relatives. 5.2 Genetic Variation in Barn Owl Populations The multilocus probes Jeffreys' 33.15 and per were successfully used for DNA fingerprinting of barn owls from BC, Utah and California. These probes yielded sufficient variation at the minisatellite loci to assess the general level of relatedness both within and between populations. The samples from the BC barn owl population, particularly the siblings, are less variable than the samples from the California and Utah populations, indicating that barn owls in BC are more closely related to one another than are populations in California and 32 Utah. This is further magnified by the fact that the Utah and California samples came from smaller areas than did the BC population. In designing the layout of DNA fingerprints used in this study, care was taken to ensure that individuals representing all areas of the population were included on each gel. Individual barn owls from close localities were not placed on the same gel. In the Utah and California populations, individuals run on each gel were from nest sites that were closer together than in the BC population. In all three populations, unrelated individuals were taken from different sibling groups. For BC and Utah, however, a few additional birds not used in sibling comparisons were also included to increase the sample size. Because of these conditions, the reduced variation in the BC population may be reduced even further if the samples had been restricted to a smaller portion of the population. This, however, will also depend on the density of breeding barn owls in the three population, which is known to vary greatly with habitat quality (Marti 1992). Since there was no available measure of density of barn owls in the three populations, it is more useful to look at band sharing among siblings as the relationship between individuals is known to be the same in all cases. In the case of unrelated individuals examined with the per probe, there was no significant difference in band sharing between the Utah and BC populations. This may reflect the different part of the genome that is examined with this probe compared with Jeffreys' 33.15. The trends, however, were the same with either probe, with genetic variation lowest in BC, followed by Utah and then California. Sibling band sharing is significantly higher in BC than in both California and Utah 33 for both probes, confirming that there is less genetic variation in the BC samples. The difference between sibling band sharing and unrelated band sharing is much greater in BC than in the other two populations, perhaps because blood samples were collected from a bigger area in BC than the other two sites. In the California population, unrelated individuals were taken from each of the sibling groups, whereas in BC and Utah unrelated individuals also included additional birds that were not run on the sibling gels. The difference in band sharing may also reflect a fragmented habitat with a few long-lived and productive breeding pairs and restricted dispersal of young. It has been suggested (Mayr 1963) that peripheral populations may be more fragmented than populations in the centre of the range because the peripheral habitat tends to be poorer overall. In fact, reduced genetic variation at the edge of a species' range has been suggested by a number of authors (Mayr 1963, Dobzhansky et al. 1963). Leung and Cheng (1994) found less genetic variability at 24 loci using protein electrophoresis at the northern range of the Cascade mantled ground squirrel (Spermophilus saturatus) than was seen in more central populations. BC barn owls are at the northern extent of the North American range and show reduced genetic variability when compared to the more central California and Utah populations. The founder effect describes the establishment of a new population by a few original founders which carry only a fraction of the total genetic variation of the parental population (Mayr 1963). Barn owls were first recorded in BC near the mouth of the Fraser River in 1909; the first breeding record was in the same area in 1941 (Campbell et al. 1990). Thus, barn owls are a relatively new species to 34 BC. The barn owl population in BC was presumably founded by a small number of birds that ventured north. Because the conditions at the northern edge of barn owl range are severe, especially in the winter, only a limited number of genotypes may be able to survive (Mayr 1963). Therefore, gene flow with more central populations may have decreased, resulting in a further reduction of genetic variation in the peripheral population. Extra-pair copulations (EPCs), if they were occuring in any of the populations studied, could cause a reduction in the band sharing values between siblings. At this point in time, there is no information on whether EPC occurs in barn owls (Marti 1992). Our examination of one nest with two consecutive clutches did not show any evidence that EPC had occurred. However, Peter Bloom (pers. comm.) has observed up to ten pairs of barn owls nesting in the same barn on the California study site. High densities of breeding individuals have been linked to an increased incidence of EPCs in some bird populations (Westneat et al. 1990). Typical band sharing values for unrelated individuals in natural populations that are not genetically impoverished lie in the range of 0.1-0.35 (Amos et al. 1992). However, population sizes and scoring rules in the different studies vary, reducing the accuracy of band sharing comparisons among different studies. Given these warnings, the band sharing values arrived at for the three different barn owl populations range from 0.20 to 0.29, within the general range found for other species. While the BC barn owl population shows less variation than those in California and Utah, it is still within a "normal" range. However, the smaller gene pool in BC means that genetic variation can 35 be lost at a faster rate than in either California or Utah even if the rate of loss of breeding and foraging habitat is the same. Comparisons of band sharing between populations suggest that California and Utah barn owls are more closely related to one another than to BC barn owls. The BC population is genetically closer, however, to Utah than it is to California. This suggests the east-west movement of barn owls may be more common than northward movement, perhaps explaining why there is limited recruitment of barn owls into the BC population from the south. DNA fingerprint bands of similar mobility in unrelated individuals are not necessarily isoallelic (Hill 1987), which is especially important to consider when comparing between the three different populations. However, any overestimation of shared alleles should be equal in pairwise comparisons of the three populations as they are approximately equal distances apart. This study provids preliminary genetic evidence of a monogamous mating system in barn owls. Two clutches from a single nest site in BC were sampled during one breeding season, yielding band sharing values indicating full sibship. This suggests, as suspected, that barn owls remain with a mate throughout the breeding season and perhaps throughout their lifetime (Taylor 1994, Marti 1992). Obviously a more detailed study of clutches both within and between breeding seasons at nest sites that are consistently used by barn owls is required to get solid genetic evidence of their mating system. 36 5.3 Conclusions DNA fingerprinting has only recently been used as a tool in population level studies (Gilbert et al. 1990, Reeve et al. 1990, Bruford et al. 1992, Lehman et al. 1992, Triggs et al. 1992, Zeh et al. 1992, Blanchetot and Gooding 1993, Timms et al. 1993, Grunder et al. 1994). DNA fingerprinting is a useful tool to assess the general relatedness and inbreeding in rare or endangered populations of a species provided there are other non-inbred populations with which to compare. In order to know if levels of band sharing are unique to a population, it is necessary to look at a number of different populations of the species to ensure differences in band sharing are not inherent to the population structure of the particular species (Triggs et al. 1992, Timms et al. 1993). Barn owls have only been in BC for short time, yet BC is now home to the only barn owl population in Canada. The grassland habitat that is required by barn owls is also important for a number of other wildlife species in the Fraser Valley, including short-eared owls (Asioflammeus), red-tailed hawks (Buteo jamaicensis), northern harriers (Circus cyaneus), great blue herons (Ardea herodias) and many species of shorebirds, waterfowl and songbirds (Butler 1992, Andrusiak 1994). Barn owls, however, are the only species currently listed by COSEWIC as a species of special concern. As such, barn owls may be used as an idicator species for this open field habitat. The BC barn owl population is more genetically isolated than the other North American barn owl populations examined. Along with this isolation, and perhaps due to their existence at the periphery of the North American population, BC barn owls have a more limited gene pool than other populations. This limited genetic base has the 37 potential to create problems associated with inbreeding as barn owl nesting and hunting habitat in BC decreases. Though most natural populations strike a balance between inbreeding and outbreeding (Bateson 1978), the BC barn owl population is begining to lean towards the side of inbreeding. As habitat decreases, it can be expected that genetic variation decrease further, which may lead to a loss of fitness and adaptability which may eventually affect the survival of the population (Keller et al. 1994, Partridge and Bruford 1994). 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Biol. 98:503-517. Stewart, P.A. 1980. Population trends of barn-owls in North America. Am. Birds 34:698-700. Taylor , I. 1994. Barn owls: Predator-prey relationships and conservation. Cambridge: Cambridge University Press. Timms, P., J. Kato, M. Maugeri, and N. White. 1993. DNA fingerprint analysis of a free-range local population. Biochem. Genetics 31:363-374. Triggs, S.J., M.J. Williams, S.J. Marshall, andG.K. Chambers. 1992. Genetic structure of Blue Duck (Hymenolaimus malacorhynchos) populations revealed by DNA fingerprinting. Auk 109:80-89. Vassart, G., M. Georges, R. Monsieur, H. Brocas, A.S. Lequarre, andD. Christophe. 1987. A sequence in M13 phage detects hypervariable minisatellites in human and animal DNA. Science 235:683-684. Westneat, D.F. 1990. Genetic parentage in the indigo bunting: a study using DNA fingerprinting. Behav. Ecol. Sociobiol. 27:67-76. Westneat, D.F., W.A. Noon, H.K. Reeve, and C.F. Aquadro. 1988. Improved hybridization conditions for DNA 'fingerprints' probed with M13. Nucleic Acids Res. 16:4161. Westneat, D.F. , P.W. Sherman, and M.L. Morton. 1990. The ecology and evolution of extra-pair copulations in birds. In Current Ornithology, volume 7, edited by D.M. Power. New York: Plenum Press. Wetton, J.H., R.E. Carter, D.T. Parkin, and D. Walters. 1987. Demographic study of a wild house sparrow population by DNA fingerprinting. Nature 327:147-149. 44 Zen, D.W., J.A. Zen, M.A. Coffroth, and E. Bermingham. 1992. Population-specific DNA fingerprints in a neotropical pseudoscorpion (Cordylochernes scorpioides). Heredity 69:201-208. 45 Appendix I Organochlorine (OC) and Polychlorinated Biphenyl (PCB) Assays of Barn Owl Livers Environmental pollutants such as organochlorines (OCs) in pesticides and polychlorinated biphenyls (PCBs) can lower productivity and are even lethal in birds (Klaas et al. 1978, Campbell and Campbell 1983, Sierra and Santiago 1987, Noble et al. 1993). Because they are at the top of the food chain, raptors and other predatory animals are especially susceptible (Noble and Elliott 1990, Noble et al. 1993). Though pesticides containing OCs have not been legally allowed in Canada or the United States since the early 1970s, their use has continued in many developing countries (Noble et al. 1993, Elliott et al. 1994, Elliott and Martin 1994). Other toxic compounds are still found in currently registered insecticides, and industrial compounds such as PCBs continue to leak into the environment (Noble et al. 1993, Elliott et al. 1994, Elliott and Martin 1994). Therefore, although most research has shown a general trend of reduction in OC residues, high levels of residues are still reported in North American wildlife (Noble and Elliott 1990, Elliott et al. 1994). In a recent British study (Newton et al. 1991), 8.8% of barn owl (Tyto alba) deaths in that country were due to OC poisoning. Because of the extreme negative effects also seen in other raptor species such as the peregrine falcon (Falco peregrinus), bald eagle (Haliaeetus leucocephalus) and osprey (Pandion haliaetus) (Noble and Elliott 1990, Elliott and Martin 1994), Campbell and Campbell (1983) 46 recommended that barn owls be periodically monitored, once every five years, for toxic chemical residues in their tissue. Methods Collection of liver samples In the fall of 1993, 20 dead barn owls were obtained from the BC Ministry of the Environment for analysis. These birds were brought into the Ministry office by members of the public or by rehabilitation centres and stored frozen at -4 °C. The birds were from throughout the BC barn owl range, from sites ranging from Richmond to Chilliwack. Livers are the major site of toxic substance metabolism and are the first organs exposed following absorption from the gastrointestinal tract (Noble et al. 1993), allowing even minute quantities of contaminants to be detected. A random sample of nine birds were dissected for a concurrent study involving internal parasites. Of these, five had livers that were in good enough condition for a toxic analysis to be completed; some livers were damaged from the method of death of the owl or were in poor shape due to freezing. The acceptable livers were removed and stored at -4 °C. These livers, along with four frozen barn owl livers (from the Canadian Wildlife Service) from the same range were sent to the Canadian Wildlife Service (CWS) in Ottawa for toxic chemical analysis. Analysis of liver samples for OCs and PCBs In October of 1994, the nine barn owl livers were sent to the National Wildlife Research Centre, CWS, Ottawa for analyses by the procedure described in CWS Report 47 87-00. Briefly, frozen samples were thawed and ground with anhydrous Na2S04 until free flowing. The samples were column extracted with 50% CH2C12 in hexane (v/v), cleaned up and separated on deactivated Florisil and analyzed by capillary column gas liquid chromatography / ECD. Results & Discussion Levels of organochlorine and PCB residues in barn owl livers are presented in Table A - l . The levels of several OC and PCB residues in barn owl livers are compared with those measured for BC barn owls in 1975 (Campbell and Campbell 1983) and in 1985 (Noble et al. 1993) in Figure A - l . The two previous studies used the same method of analysis as this one. OC and PCB residues in barn owl livers have consistently dropped since 1975. This also represents a concurrent decrease in environmental residues. The levels of residues found in BC barn owls have never been of great concern to wildlife officials as they are extremely low when compared to levels in some other high risk species (J. Elliott pers. comm.). Wildlife rehabilitators in the Lower Mainland area also report that pesticide poisoning of barn owls is rare (L. Short, pers. comm., M. Tolksdorf, pers. comm.) However, the routine monitoring of levels does give an indication of residue levels in a species that is not being adversely affected. 48 5 a. I s ."2 "35 J ' Si U u pa 3 •-9 1 Q "a a g a. a ^ O o >/•> o o p o m o o\ vo o d o o 8 © P d 8 o d s o O O O ON 00 00 vo CD 8 2 o <D t-i IS g c <u 8 § 3 P x X! I I I I . . si II •I * * a 49 MIREX Organochlorine Figure A - l . Organochlorine and PCB residues in BC barn owl livers. 50 References Campbell, E.C. and R.W. Campbell. 1983. Status report on the Common Barn-Owl (Tyto alba) in Canada - 1982. Committee on the Status of Endangered Wildlife in Canada, BC Ministry of the Environment. Elliott, J.E. and P. A. Martin. 1994. Chlorinated hydrocarbons and shell thinning in eggs of (Accipiter) hawks in Ontario, 1986-1989. Environ. Pollut. 86:189-200. Elliott, J.E., P.A. Martin, T.W. Arnold, and P.H Sinclair. 1994. Organochlorines and reproductive success of birds in orchard and non-orchard areas of central British Columbia, Canada, 1990-91. Arch. Environ. Contain. Toxicol. 26:435-443. Klaas, E .E . , S.N. Wiemeyer, H.M. Ohlendorf, and D.M. Swineford. 1978. Organochlorine residues, eggshell thickness, and nest success in barn owls from the Chesapeake Bay. Estuaries 1:46-53. Newton, I., I. Wyllie & A. Asher. 1991. Mortality causes in British Barn Owls, Tyto alba, with a discussion of aldrin-dieldrin poisoning. Ibis 133:162-169. Noble, D.G. and J.E. Elliott. 1990. Levels of contaminants in Canadian raptors, 1966 to 1988; effects and temporal trends. Canadian Field-Naturalist. 104:222-243. Noble, D.G. , J.E. Elliott, and J.L. Shutt. 1993. Environmental contaminants in Canadian raptors, 1965-1988. Can. Wildl. Serv. Tech. Rep. Ser. Ottawa. No.91, 225pp. Sierra, M . and D. Santiago. 1987. Organochlorine pesticide levels in barn owls collected in Leon, Spain. Bull. Environ. Contam. Toxicol. 38:261-265. 51 Appendix II Actual Output From NTSYS-pc MXCOMP (Matrix Comparisons) Analyses = = = = = = = = = = = = = = = MXCOMP = = = = = 7/12/95 12:52 = = = = = = = = = = = = = = = X matrix: A:BUNPROBB.TXT "BC UNRELATED INDIVIDUALS: Probe 33.15 vs per" type=3, size=35 by 35, nc= 9.99900000000000E+0003 Y matrix: A:BUNPROBA.TXT type=3, size=35 by 35, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 289 Mean X = 2.52941 SSx = 72.00000 Mean Y = 0.30792 SSy = 4.56155 Tests for association: Matrix correlation: r = 0.04346 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 0.760 Prob. random Z < obs. Z: p = 0.7762 Out of 50 random permutations: 40 were < Z, 0 were = Z, and 10 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z > = observed Z] = 0.2200 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/13/95 20:06 = = = = = = = = = = = = = = = X matrix: A:BCB2.TXT "BC SIBS: Probe 33.15 vs per" type=3, size=48 by 48, nc= 9.99900000000000E + 0003 Y matrix: A:BCA2.TXT type=3, size=48 by 48, nc= 9.99900000000000E + 0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 75 Mean X = 2.49333 SSx = 18.74667 Mean Y = 0.66040 SSy = 1.69649 Tests for association: Matrix correlation: r = -0.02745 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -0.875 Prob. random Z < obs. Z: p = 0.1909 Out of 200 random permutations: 38 were < Z, 0 were = Z, and 162 > Z (The observed comparison is not included in these counts.) The one-tail probability is: pfrandom Z < = observed Z] = 0.1950 52 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/12/95 12:55 X matrix: A:UUNPROBB.TXT "UTAH UNRELATED INDIVIDUALS: Probe 33.5 vs per" type=3, size=32 by 32, nc= 9.99900000000000E+0003 Y matrix: A:UUNPROBA.TXT type=3, size=32 by 32, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 240 Mean X = 4.50000 SSx = 60.00000 Mean Y = 0.27875 SSy = 4.04363 Tests for association: Matrix correlation: r = 0.27157 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 3.711 Prob. random Z < obs. Z: p = 0.9999 Out of 50 random permutations: 50 were < Z, 0 were = Z, and 0 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z > = observed Z] = 0.0200 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/12/95 12:54 X matrix: A:UPROBEB.TXT "UTAH SffiS Probe 33.5 vs per" type=3, size=26 by 26, nc= 9.99900000000000E+0003 Y matrix: A:UPROBEA.TXT type=3, size=26 by 26, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 22 Mean X = 4.50000 SSx = 5.50000 Mean Y = 0.45318 SSy = 1.01348 Tests for association: Matrix correlation: r = 0.19695 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 3.532 Prob. random Z < obs. Z: p = 0.9998 Out of 50 random permutations: 50 were < Z, 0 were = Z, and 0 > Z (The observed comparison is not included in these counts.) The one-tail probability is: pfrandom Z > = observed Z] = 0.0200 53 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/12/95 12:56 X matrix: A:CUNPROBB.TXT "CALIF UNRELATED INDIVIDUALS: Probe 33.15 vs per" type=3, size=12 by 12, nc= 9.99900000000000E+0003 Y matrix: A:CUNPROBA.TXT type=3, size=12 by 12, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 30 Mean X = 6.50000 SSx = 7.50000 Mean Y = 0.21400 SSy = 0.73872 Tests for association: Matrix correlation: r = 0.05523 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 0.387 Prob. random Z < obs. Z: p = 0.6508 Out of 50 random permutations: 26 were < Z, 0 were = Z, and 24 > Z (The observed comparison is not included in these counts.) The one-tail probability is: pfrandom Z > = observed Z] = 0.5000 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/12/95 12:56 X matrix: A: CALPROBB.TXT "CALDJORNIA SD3S: Probe 33.15 vs per" type=3, size=28 by 28, nc= 9.99900000000000E + 0003 Y matrix: A: CALPROBA.TXT type=3, size=28 by 28, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 14 Mean X = 6.50000 SSx = 3.50000 Mean Y = 0.46786 SSy = 0.45644 Tests for association: Matrix correlation: r = -0.04351 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -0.845 Prob. random Z < obs. Z: p = 0.1991 Out of 50 random permutations: 7 were < Z, 0 were = Z, and 43 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z < = observed Z] = 0.1600 54 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/12/95 12:24 X matrix: A:BC33B.TXT "BC SIBS vs BC UNREL: Probe 33.15" "bcsibs=2.00; bcunrel=5.00 type=3, size=48 by 48, nc= 9.99900000000000E+0003 Y matrix: A:BC33A.TXT type=3, size=48 by 48, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 183 Mean X = 4.22951 SSx = 314.36066 Mean Y = 0.39563 SSy = 8.28690 Tests for association: Matrix correlation: r = -0.74738 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -17.798 Prob. random Z < obs. Z: p = 0.0000 Out of 50 random permutations: 0 were < Z, 0 were = Z, and 50 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z < = observed Z] = 0.0200 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 16:57 X matrix: A:BCPERB.TXT "BC SIBS vs. BC UNRELATED: Probe per" "bcsibs=2.00; be unrel=5.00 type=3, size=51 by 51, nc= 9.99900000000000E+0003 Y matrix: A:BCPERA.TXT type=3, size=51 by 51, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 206 Mean X = 3.87660 SSx = 751.44662 Mean Y = 0.39553 SSy = 7.04649 Tests for association: Matrix correlation: r = -0.74405 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -19.044 Prob. random Z < obs. Z: p = 0.0000 55 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:48 X matrix: A:UT33B.TXT "UTAH SIBS VS UTAH UNREL: Probe 33.15" "utsibs=3.00; utunrel=6.00 type=3, size=29 by 29, nc= 9.99900000000000E+0003 Y matrix: A:UT33A.TXT type=3, size=29 by 29, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 131 Mean X = 5.74809 SSx = 90.68702 Mean Y = 0.25756 SSy = 2.57502 Tests for association: Matrix correlation: r = -0.33116 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -6.284 Prob. random Z < obs. Z: p = 0.0000 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/28/95 23:21 X matrix: A:UTPERB.TXT "UTAH SIBS VS UTAH UNREL: Probe per" "utsibs=3.00; utunrel=6.00 type=3, size=29 by 29, nc= 9.99900000000000E + 0003 Y matrix: A:UTPERA.TXT type=3, size=29 by 29, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 131 Mean X = 5.53779 SSx = 305.72386 MeanY= 0.32924 SSy = 2.75872 Tests for association: Matrix correlation: r = -0.33241 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -6.340 Prob. random Z < obs. Z: p = 0.0000 56 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/28/95 23:24 X matrix: A:CAL33B.TXT "CALIFORNIA SIBS VS UNREL; Probe 33.15" "calsib=4.00; calunrel=7.00 type=3, size=20 by 20, nc= 9.99900000000000E+0003 Y matrix: A:CAL33A.TXT type=3, size=20 by 20, nc= 9.99900000000000E + 0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 22 Mean X = 6.04545 SSx = 42.95455 Mean Y = 0.29136 SSy = 0.88906 Tests for association: Matrix correlation: r = -0.62646 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -8.149 Prob. random Z < obs. Z: p = 0.0000 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/28/95 23:23 X matrix: A:CALPERB.TXT "CALIFORNIA SIBS VS UNREL; Probe per" "calsibs=4.00; calunrel=7.00 type=3, size=20 by 20, nc= 9.99900000000000E+0003 Y matrix: A: CALPERA.TXT type=3, size=20 by 20, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 22 Mean X = 6.04545 SSx = 42.95455 Mean Y = 0.29818 SSy = 0.92073 Tests for association: Matrix correlation: r = -0.54035 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -7.092 Prob. random Z < obs. Z: p = 0.0000 57 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:42 X matrix: A:CB33B.TXT "BC UNREL VS CALIF UNREL: Probe 33.15" "bc=5.00; cal=7.00 type=3, size=23 by 23, nc= 9.99900000000000E+0003 Y matrix: A:CB33A.TXT type=3, size=23 by 23, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 151 Mean X = 5.19868 SSx = 54.03974 Mean Y = 0.29252 SSy = 2.94604 Tests for association: Matrix correlation: r = -0.20729 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -2.507 Prob. random Z < obs. Z: p = 0.0061 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:43 X matrix: A:CBPERB.TXT "BC UNREL VS CALIF UNREL: Probe per" "bc=5.00; calif=7.00 type=3, size=24 by 24, nc= 9.99900000000000E+0003 Y matrix: A:CBPERA.TXT type=3, size=24 by 24, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 168 M e a n X = 5.17857 SSx = 54.64286 Mean Y = 0.30500 SSy = 2.58160 Tests for association: Matrix correlation: r = -0.20796 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -2.923 Prob. random Z < obs. Z: p = 0.0017 58 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:45 X matrix: A:BU33B.TXT "BC UNREL VS. UTAH UNREL: Probe 33.15" "bc=5.00; Utah=6.00 type=3, size=33 by 33, nc= 9.99900000000000E+0003 Y matrix: A:BU33A.TXT type=3, size=33 by 33, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 256 Mean X = 5.46875 SSx = 63.75000 Mean Y = 0.27465 SSy = 4.44617 Tests for association: Matrix correlation: r = -0.22202 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -3.107 Prob. random Z < obs. Z: p = 0.0009 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:44 X matrix: A:BUPERB.TXT "BC UNREL vs UTAH UNREL: Probe per" "bc=6.00; Utah=6.00 type=3, size=34 by 34, nc= 9.99900000000000E + 0003 Y matrix: A:BUPERA.TXT type=3, size=34 by 34, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 273 Mean X = 5.43956 SSx = 67.25275 Mean Y = 0.31348 SSy = 4.07139 Tests for association: Matrix correlation: r = 0.00377 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 0.072 Prob. random Z < obs. Z: p = 0.5286 59 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:19 X matrix: A:UC33B.TXT "UTAH UNREL VS CALIF UNREL: Probe 33.15" "utah=3.00; calif=4.00 type=3, size=22 by 22, nc= 9.99900000000000E+0003 Y matrix: A:UC33A.TXT type=3, size=22 by 22, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 135 Mean X = 6.11111 SSx = 13.33333 Mean Y = 0.23926 SSy = 2.07013 Tests for association: Matrix correlation: r = -0.09686 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -1.248 Prob. random Z < obs. Z: p = 0.1060 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:24 X matrix: A:UCPERB.TXT "UTAH UNREL VS CALIF UNREL: Probe per" "utah=6.00;calif=7.00 type=3, size=22 by 22, nc= 9.99900000000000E+0003 Y matrix: A:UCPERA.TXT type=3, size=22 by 22, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 135 Mean X = 6.11111 SSx = 13.33333 Mean Y = 0.30385 SSy = 2.54240 Tests for association: Matrix correlation: r = -0.20916 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -2.657 Prob. random Z < obs. Z: p = 0.0039 60 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:02 X matrix: A:BUSIB33B.TXT "BC SIBS vs UTAH SIBS: Probe 33.15" "BC=2.00; UTAH=3.00 type=3, size=44 by 44, nc= 9.99900000000000E+0003 Y matrix: A:BUSIB33A.TXT type=3, size=44 by 44, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 58 Mean X = 2.18966 SSx = 8.91379 Mean Y = 0.61776 SSy = 2.30441 Tests for association: Matrix correlation: r = -0.50204 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -15.093 Prob. random Z < obs. Z: p = 0.0000 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/21/95 17:03 X matrix: A:BUSIBPB.TXT "BC SIBS vs UTAH SIBS: Probe per" "BC=2.00; UTAH=3.00 type=3, size=46 by 46, nc= 9.99900000000000E + 0003 Y matrix: A:BUSIBPA.TXT type=3, size=46 by 46, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 64 Mean X = 2.17188 SSx = 9.10938 Mean Y = 0.60984 SSy = 1.53210 Tests for association: Matrix correlation: r = -0.33681 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -10.654 Prob. random Z < obs. Z: p = 0.0000 61 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/28/95 23:28 X matrix: A:CBSIB33B.TXT "BC SIBS vs CALIFORNIA SIBS; Probe 33.15 "BC=2.00; CAL=4.00 type=3, size=45 by 45, nc= 9.99900000000000E+0003 Y matrix: A:CBSIB33A.TXT type=3, size=45 by 45, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 50 Mean X = 2.12000 SSx = 11.28000 Mean Y = 0.64240 SSy = 1.85251 Tests for association: Matrix correlation: r = -0.48879 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -15.321 Prob. random Z < obs. Z: p = 0.0000 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/28/95 23:29 X matrix: A:CBSIBPB.TXT "BC SIBS vs CALIFORNIA SIBS; Probe per "BC=2.00; CAL=4.00 type=3, size=47 by 47, nc= 9.99900000000000E + 0003 Y matrix: A: CBSIBPA.TXT type=3, size=47 by 47, nc= 9.99900000000000E + 0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 57 Mean X = 2.14035 SSx = 14.87719 Mean Y = 0.61614 SSy = 1.28435 Tests for association: Matrix correlation: r = -0.42302 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -13.857 Prob. random Z < obs. Z: p = 0.0000 62 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/28/95 23:30 X matrix: A:UCSIBPB.TXT "UTAH SIBS VS CALIFORNIA SIBS; Probe per "UTAH 3.00; CALIF 4.00 type=3, size=27 by 27, nc= 9.99900000000000E+0003 Y matrix: A:UCSIBPA.TXT type=3, size=27 by 27, nc= 9.99900000000000E + 0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 18 Mean X = 3.38889 SSx = 4.27778 Mean Y = 0.48167 SSy = 0.65305 Tests for association: Matrix correlation: r = -0.09074 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -1.694 Prob. random Z < obs. Z: p = 0.0451 = = = = = = = = = = = = = = = MXCOMP = = = = = 4/28/95 23:30 X matrix: A:UCSIB33B.TXT Comments: "UTAH SIBS VS CALIFORNIA SIBS; Probe 33.15 "UTAH 3.00; CALIF 4.00 type=3, size=27 by 27, nc= 9.99900000000000E+0003 Y matrix: A:UCSIB33A.TXT type=3, size=27 by 27, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 18 Mean X = 3.33333 SSx = 4.00000 Mean Y = 0.43611 SSy = 0.80003 Tests for association: Matrix correlation: r = 0.32050 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 5.994 Prob. random Z < obs. Z: p = 1.0000 63 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/13/95 20:16 X matrix: A:33B2.TXT "BC-UTAH VS BC-CALD7: Probe 33.15" type=3, size=51 by 51, nc= 9.99900000000000E+0003 Y matrix: A: 33A2.TXT type=3, size=51 by 51, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 175 Mean X = 2.91429 SSx = 13.71429 Mean Y = 0.18749 SSy = 2.38449 Tests for association: Matrix correlation: r = 0.13855 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 4.554 Prob. random Z < obs. Z: p = 1.0000 Out of 200 random permutations: 200 were < Z, 0 were = Z, and 0 > Z (The observed comparison is not included in these counts.) The one-tail probability is: pfrandom Z > = observed Z] = 0.0050 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/13/95 20:15 X matrix: A:PBB2.TXT "BC-UTAH VS BC-CALDJ: Probe per" type=3, size=49 by 49, nc= 9.99900000000000E+0003 Y matrix: A:PBA2.TXT type=3, size=49 by 49, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 164 Mean X = 2.89220 SSx = 20.27641 Mean Y = 0.25177 SSy = 2.84859 Tests for association: Matrix correlation: r = 0.06101 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 1.921 Prob. random Z < obs. Z: p = 0.9726 Out of 200 random permutations: 193 were < Z, 0 were = Z, and 7 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z > = observed Z] = 0.0400 64 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/11/95 20:22 X matrix: A:33BC-UCB.TXT "BC-CALIF VS UTAH-CALIF: Probe 33.15" type=3, size=22 by 22, nc= 9.99900000000000E+0003 Y matrix: A:33BC-UCA.TXT type=3, size=22 by 22, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 60 Mean X = 3.20000 SSx = 57.60000 Mean Y = 0.18167 SSy = 0.90543 Tests for association: Matrix correlation: r = 0.39603 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 5.326 Prob. random Z < obs. Z: p = 1.0000 Out of 250 random permutations: 250 were < Z, 0 were = Z, and 0 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z > = observed Z] = 0.0040 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/11/95 20:28 X matrix: A:PBC-UCB.TXT "BC-CALIF VS UTAH-CALIF: Probe per" type=3, size=21 by 21, nc= 9.99900000000000E + 0003 Y matrix: A:PBC-UCA.TXT type=3, size=21 by 21, nc= 9.99900000000000E + 0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N 54 Mean X = 3.11111 SSx = 53.33333 Mean Y = 0.24185 SSy = 0.63221 Tests for association: Matrix correlation: r = 0.15652 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 2.103 Prob. random Z < obs. Z: p = 0.9823 Out of 250 random permutations: 249 were < Z, 0 were = Z, and 1 > Z (The observed comparison is not included in these counts.) The one-tail probability is: pfrandom Z > = observed Z] - 0.0080 65 = = = = = = = = = = = = = = = = MXCOMP = = = = = 7/13/95 20:13 X matrix: A: 33BB2.TXT "BC-UTAH VS UTAH-CALIF: Probe 33.15" type=3, size=51 by 51, nc= 9.99900000000000E+0003 Y matrix: A: 33BA2.TXT type=3, size=51 by 51, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 172 Mean X = 3.11628 SSx = 17.67442 Mean Y = 0.19047 SSy = 2.44856 Tests for association: Matrix correlation: r = 0.06547 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = 2.149 Prob. random Z < obs. Z: p = 0.9842 Out of 200 random permutations: 194 were < Z, 0 were = Z, and 6 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z > = observed Z] = 0.0350 = = = = = = = = = = = = = = = MXCOMP = = = = = 7/13/95 20:11 X matrix: A:PUB2.TXT "BC-UTAH VS UTAH-CALIF: Probe per" type=3, size=50 by 50, nc= 9.99900000000000E+0003 Y matrix: A:PUA2.TXT Comments: "bc-utah vs utah-calif per type=3, size=50 by 50, nc= 9.99900000000000E+0003 X matrix stored in RAM memory. Y matrix stored in RAM memory. N = 169 Mean X = 3.10249 SSx = 25.40736 Mean Y = 0.25444 SSy = 2.85877 Tests for association: Matrix correlation: r= -0.04980 (= normalized Mantel statistic Z) Approximate Mantel t-test: t = -1.582 Prob. random Z < obs. Z: p = 0.0568 Out of 200 random permutations: 12 were < Z, 0 were = Z, and 188 > Z (The observed comparison is not included in these counts.) The one-tail probability is: p[random Z < = observed Z] = 0.0650 

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