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Dispersal and development of the striped ambrosia beetle trypodendron lineatum (oliv.) in industrial… McIntosh, Rory L. 1994

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DISPERSAL AND DEVELOPMENT OF THE STRIPED AMBROSIA BEETLE TRYPODENDRON LINEA TUM (OLIV.) IN INDUSTRIAL SORTING AND STORAGE AREAS by Rory L. McIntosh B. Sc. F., University of New Brunswick, Fredencton N.B., 1986. A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Department of Forest Sciences) We accept this thesis as conforming to the required standard  THE UNWERSITY OF BRITISH COLUMBIA September 1994 © Rory L. McIntosh, 1994  In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Ubrary 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 of  fi,?6T  S/&’JEr  The University of British Columbia Vancouver, Canada Date  DE-6 (2/88)  ?  5’’  i-er  /39 4-  U  ABSTRACT  Ambrosia beetles, in particular the striped ambrosia beetle Trypodendron lineatum (Olivier.) [Coleoptera: Scolytidae] cause serious degrade to logs harvested in British Columbia. Losses to the Coastal forest industry have been estimated at $120 million per annum. Although 75% of the damage occurs in the forest, 25% occurs while logs are at sorting and storage areas. Populations of ambrosia beetles are spread in logs transported into these areas.  Industrial sites become  contaminated when beetles egress stored logs and fly to the forest margin to overwinter. These individuals comprise the spring flight the following year and will attack any susceptible stored logs at that time.  Mass trapping beetles is an accepted component of integrated pest management around industrial sites.  Traps baited with lineatin, cL-pinene and ethanol are commonly used.  A Latin square  experiment was conducted to test, these components singly, and in combination to elucidate which component or combination of components are best to trap “sister flight” beetles. Results demonstrated that c-pinene and ethanol did not significantly enhance trapping performance and that lineatin is the only significant trap bait for trapping “sister flight” beetles. Lineatin-baited traps located in the Foreshore Park area of the Pacific Spirit Park in Vancouver, were used to trap 1993 sister flight beetles.  The same traps were re-baited in 1994 to monitor the mass flight.  There was a positive correlation of mass attack catches with sister flight trap catches.  Temperature related heat sum model experiments of T lineatum development were conducted at the University of British Columbia in Vancouver. Beetles were inoculated into log bolts left to develop in controlled conditions at 18, 20, 25 and 30 °C, under ambient conditions at the U.B.C. South Campus. A threshold temperature of 12.34 °C was derived and used in the calculation of accumulated heat sum. Sister flight activity was indicated by presence of empty niches after 65 days or 324 degree days. Internal log temperatures were monitored at the South Campus. High mortality precluded brood development in the top and west quadrants of the log where  111  temperatures commonly exceeded 35 °C. Brood development and survivorship were greater in the bottom and eastern quadrants of the log.  It was recommended that lineatin alone is sufficient for trapping sister flight beetles. Additional lineatin-baited traps should be used to develop a database to derive a predictive model to determine mass flight numbers from sister flight trap catches to help focus fhture mass trapping operations. The threshold temperature of 12.34 °C could be used to derive universal model of T lineatum development. Accumulated heat sum of 324 units could be used to predict sister flight. Key Words:  ambrosia beetle; degree-day; development threshold; dry-land sorts; heat sum; mass trapping; semiochemicals.  iv  TABLE OF CONTENTS  Abstract Table of Contents  iv  List of Tables  vii  List of Figures  ix  Acknowledgments  xi  CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW 1.1. Introduction  1  1.2. Literature Review 1.2.1. Host Selection Criteria 1.2.2. Life Cycle of the Striped Ambrosia Beetle Overwintering  6 7 9 9  Pioneer Flight  12  Flight Dispersal  12  Brood Production  15  1.2.3. Flight Response 1.2.4. Management and Control  23  1.3. Summary  24 31  CHAPTER 2. POPULATION MONITORING WITH SEMIOCHEMICALS 2.1. Introduction  33  2.2. Latin Square Test 1992 2.2.1. The Study Area 2.2.2. Methods and Materials -  35 36 37  2.2.3.  Experimental Design  39  2.2.4.  Results Discussion and Conclusions  40  2.2.5.  42  V  2.3. Latin Square Test 1993 2.3.1. The Study Area -  42 42  2.3.2.  Methods and Materials  43  2.3.3.  Experimental Design  43  2.3.4.  Results  43  2.3.5.  Discussion and Conclusions  47  2.4. Trapping Correlation Study 1993-1994 2.4.1. Introduction 2.4.2.  48 48  2.4.3.  Spring Mass Flight versus Sister Flight The Study Area  52  2.4.4.  Methods and Materials  52  2.4.5.  Results Discussion and Conclusions  54  2.4.6.  50  56  CHAPTER 3. DEVELOPMENT OF A DEGREE DAY MODEL 3.1. Introduction  58  3.2. Background  59  3.3. Influence of Climate on Insects  60  3.4. Degree Day Theory 3.4.1. Accumulated Heat Sum 3.4.2. Growing Degree Days  60  3.5. Insect Development Modelling  63  3.5.1.  The Biofix in Applied Degree-day Models  62 62  64  3.6. Summary  65  3.7. A Degree-Day Model for T lineatum Development 3.7.1. TheStudyArea  66  3.7.2. 3.7.3.  66  Methods and Materials Sampling Design  66  Sampling Procedure  67  Sample Preparation  69  67  v 3.7.4.  Insect Collection  70  3.7.5.  Inoculation Process  71  3.7.6.  Meteorological Measurements  72 74  3.7.7.  Environmental Chambers South Campus Determination of Threshold Temperature (T ) 0 Determination of Heat Sum Galirey and Brood Production  3.7.8. 3.7.9. 3.8. Results  3.8.1. 3.8.2. 3.8.3. 3.8.4.  3.8.5. 3.8.6. 3.8.7  74 76 77 78 78  Inoculations Environmental Chambers  78  Dissections  81  Number ofLarval Instars Calculation of Threshold Temperature (T ) 0 Calculation of Heat Sum Accumulation (DD) Thermocouple Test Log Temperatures Gallery and Brood Production  82  80  82 84 85  85 87  3.9. Discussion  90  3.9.1.  Inoculation  91 91  3.9.2.  Host Suitability Insect Compatibility Environmental Chambers Experimental Design Temperatures Inside Log  3.9.3. 3.9.4.  3.10. Conclusions and Recommendations 3.10.1. Widespread Application of the Life Stage Development Index 3.10.2. Management of Trap Bundles in Dry-land Sorting Areas 3.10.3. Further Research and Development Opportunities 3.11. Bibliography Appendices  92 94 95 96 98 99 100 101 102 113  vii  LIST OF TABLES Table  page  1-1.  Historical review of strategies explored to control T lineatum.  26  2-1.  Number of male, female and total T lineatum trapped in each treatment in the first three replicates of the 8 x 8 Latin square test at China Creek, July 1992.  40  2-2.  Transformed mean number of male and female T lineatum (± SD) trapped at China Creek between July 24-31, 1992.  41  2-3.  One-way analysis of variance of male and female T lineatum trap catches (transformed X’ = Log 10 (x+1)) at China Creek, 1992. (n = 3).  41  2-4.  Numbers of male, female and total T lineatum trapped between July 6 and August 20, 1993 in each of the eight treatments in the Foreshore area of the Pacific Spirit Park, Vancouver B.C.  44  2-5.  Analysis of variance of total male and female T lineatum trap catches in the 8 x 8 Latin square test in Vancouver B.C. (P = 0.05).  46  2-6.  Analysis of variance of male and female T lineatum trapped in Vancouver B.C. between July 6 and August 20, 1993.  46  3-1.  Mortality in three of the five rearing regimes using laboratory inoculated GVRD logs.  79  3-2.  Start dates for each of the five treatments comprised of the four temperature controlled treatments and the ambient conditions. Mean environmental chamber temperature (± SD) measured using the Campbell Scientific CR10 datalogger.  80  3-3.  Total number of galleries dissected in the environmental chambers and from the South Campus logs between May 13 and August 22, 1993.  81  3-4.  Total tally of each life stage found during dissections (n  81  number of days).  viii  3-5.  3-6.  3-7.  3-8.  Time (T ) required for 50% of each life stage to develop under 5 different 50 temperature scenarios.  84  Total number of days for brood development from the gallery development biofix to the last life stage present under the five temperature regimes from May 13 and August 22, 1993.  84  Results of the one-tailed paired-sample t test to test the significance of thermocouple placement on mean temperature measurements.  85  Comparison of the mean number of attacks, niches, and niches per attack by quadrant using the Scheffé pairwise multiple comparison test (n = 20).  89  LIST OF FIGURES Figure  ix  page  1-1.  Generalized life cycle of the striped ambrosia beetle Trypodendron lineatum.  10  1-2.  Scanning electron micrographs (50x) showing the phenological differences in head structure between: A) male; and B) female T lineatum.  16  1-3.  Typical T lineatum galleiy in sapwood of western hemlock (Tsuga heterophylla).  17  1-4.  Photomicrograph (50x) of ambrosial fungus growth from the gallery walls into the gallery opening.  19  1-5.  Life stage development ofT lineatum A) shows the white packing dust sealing in the eggs in to the egg niches; and B) shows Li and L2 instar larvae in their larval niches.  20  1-6.  Second instar larva in larval niche (40x).  21  1-7.  Late stages of development of T lineatum. A) shows pupae in their niches (3 5x); and B) shows two teneral adults in their niches (25x)  22  2-1.  Geographic location of Port Alberni (Scale 1:50,000).  37  2-2.  Location of the study area at the China Creek dryland sort near Port Alberni (Scale 1: 50,000).  38  Mean number of T lineatum trapped in the 8 x 8 Latin square study over a period between July 6 and August 20, 1993. Means labelled with the same letter are not significantly different (SNK; P < 0.05).  45  Timing of the 1993 mass attack relative to temperature in the Foreshore area of the Pacific Spirit Park, Vancouver B.C.  51  2-3.  2-4.  x 2-5.  Correlation of 1994 mass attack trap catches with 1993 sister flight trap catches in the Foreshore area of the Pacific Spirit Park, Vancouver B.C.  55  3-1.  Diurnal mean air temperature fluctuations as measured at 15 minute intervals and recorded by a Campbell Scientific CR10 datalogger in the University Endowment lands over a two day period between May 4-5, 1993..  61  3-2.  Environmental chambers used for rearing T lineatum under different temperature conditions in the controlled laboratory experiments.  68  3-3.  Environmental chamber containing log bolts with active brood production following manual inoculation with male and female T lineatum pairs.  68  34.  Lindgren® 12 unit multiple funnel trap used in T lineatum flight monitoring and insect collection.  70  3-5.  Daily temperatures for May, 1993 as measured at the Pemberton airport.  73  3-6.  Copper/Constantan thermocouples used to monitor temperature under the bark and inside the wood in four quadrats of sample logs at the south Campus location.  75  3-7.  T lineatum head capsule frequency distribution clearly showing the presence of two larval instars (n = 300).  83  3-8.  Chart showing the number of degree days above 12.34° C for first sign, 50% and last sign of each T lineatum life stage in the 18° C treatment.  86  3-9.  Diurnal log and air temperature measured at the South Campus over a two day period between June 1-2, 1993. Air temperature measurements and temperature at all four quadrants in A) the wood; and B) the bark, were taken at 30 minute intervals.  88  x ACKNOWLEDGEMENTS I would like to take this opportunity to express my gratitude to my supervisor Dr. John McLean for his enthusiasm, encouragement, support and advice in all aspects of this project. I extend my thanks to my supervisory committee Dr. Staffan Lindgren, Dr. Murray Isman and Prof Glen Young for the benefit of their advice and experience. This project was made possible through the generosity and foresight of Industrial Collaborators for whom this study was undertaken. My sincere thanks to Canadian Forest Products Ltd., MacMillan Bloedel Ltd., Weldwood Canada, and Western Forest Products. Similarly, PheroTech Inc., provided funding, expertise and assistance when approached and the assistance of Ms. Arlene Moorman and Ms. Dee Bartens was greatly appreciated. The logs used in this study were donated by the Greater Vancouver Regional District. I extend my gratitude to Paul Turner, Mill manager for C.R.B. logging of Pemberton for providing auxiliary material, the donation of which helped salvage my heat sum experiment. Assistance from Sabina Ghazarian and Jenny Heron was much appreciated, and I extend my thanks to Bruce LaHaie and Fran O’Donnell for their technical assistance and the many hours of hard work. Last but not least I would like to thank my wife Julie for her help, encouragement, patience and love throughout.  1 CHAPTER 1.  1.1.  INTRODUCTION AND LITERATURE REVIEW OF THE BIOLOGY, ECOLOGY AND MANAGEMENT OF THE AMBROSIA BEETLE TR YPODENDRON LINEA TUM (OLIVIER).  Introduction.  Insects are the most numerous of all organisms in the animal kingdom and comprise about 75% of all named animal species (Stark et a!. 1985). The diversity of insects are such that although several hundred thousand different kinds have been described, it is believed that their numbers may approach 30 million. Within the class Insecta, the Coleoptera (beetles) are known to be the largest order, containing approximately 40% of the known species in the Hexapoda. More than 250,000 species of beetles have been described, 30,000 of these occurring in Canada and the United States (Borror et at. 1989). In taxonomic nomenclature, the name Coleoptera (beetles) is derived from Greek origins [Coleo, sheath; ptera, wings] alluding to the hardened shell-like structure of the elytra  -  the modified fore-wings characteristic to this order (Stark et a!. 1985).  Because this order is so large and diverse, the beetles have been subdivided into 101 families from 19 superfamilies on the basis of morphological phenological and behavioural characteristics (Borror eta!. 1989).  Beetles vary in size, habit and habitat and many are of significant economic importance. For example, the bark beetles live and breed only in the cambial region of the bark of trees; while others such as ambrosia beetles use a three-dimensional resource boring into the sapwood of host trees (Borden 1988). Genera of ambrosia beetles are found in two families: some in the family Scolytidae and all of the Platypodidae (Coulson and Witter 1984).  Wood and Bright (1992)  catalogued 5,812 species of beetles occurring in the family Scolytidae, and 1,463 species in the family Platypodidae in the world fauna. In contrast to other members of the Scolytidae, ambrosia beetles bore into the wood of their host trees where they cultivate and feed on symbiotic ambrosial fungi (Borden 1988).  2 In British Columbia (B.C.), there are at least five different ambrosia beetle species which can affect the value of commercial timber:  The striped ambrosia beetle Trypodendron lineatum  (Olivier) [formerly Xyloterus lineatus] (Hadorn 1933; Nijholt 1979), Gnathotrichus sulcatus (LeConte), Gnathotrichus retusus (LeConte), Platypus wilsoni Swaine and Xyleborus saxeseni (Ratz). In B.C. T lineatum is by far the most abundant and damaging ambrosia beetle species and accounts for about 95% of the economic impact to coastal forest inventories. The remainder is caused equally by G. sulcatus and G. retusus (Nijholt 1979). The remaining two species: P. wilsoni and the X saxeseni, are not found as frequently in B.C. (Prebble and Graham 1957; Shore 1985).  Although damaging to the forest industry, ambrosia beetles play an important part in forest ecology (Nijholt 1979). In its natural environment, T lineatum ftilfills an important ecological role as a recycling agent.  It pioneers the process of decomposition, initiating and promoting  nutrient recycling (Lindgren 1990). T lineatum finds its niche in dead and dying timber, where it typically inhabits the sapwood of windblown and damaged trees found on the forest floor after winter storms. Beetles remain within the host for a relatively short time, leaving the log within months to the decomposing action of other wood boring insects and saprophytic fungi (Borden 1988). However, host trees killed by winds and storms are a relatively scarce resource, thus trees killed by other agents such as insect defoliators and bark-beetles or chainsaws provide an excellent and abundant source of host material susceptible to attack (Nijholt 1979). Most of the major coastal softwood species are susceptible to infestation by T lineatum, including: Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco.), western hemlock (Tsuga heterophylla (Raf) Sarg.), the true firs (A bEes spp.) and Sitka spruce (Picea sitchensis (Bong.) Carr.) (Shore 1985). However, other species, for example western red cedar Thujaplicata Donn, are inherently resistant to attack (Dyer 1963).  Speight and Wainhouse (1989) discussed  mechanisms of plant resistance to insect and disease. Non-preferred plants often contain repellent chemicals which certain insects avoid. Phytotoxic oleoresins, containing thujaplicins, can initiate a  3 non-preference response by attacking beetles. Western red cedar contains high concentrations of these phytotoxins.  In susceptible species, logs become degraded, and lumber recovery values  reduced, when the valuable clear outer portion of the logs become damaged by brood galleries and stained through the action of associated dark staining fungi introduced by attacking beetles (McLean 1985). T lineatum is considered a serious pest to the B.C. forest industry. Attacks by this insect can cause extensive degrade to high-grade logs harvested in coastal B.C. (McBride and Kinghorn 1960; Dyer 1963; Gray and Borden 1985; McLean 1985; McLean 1992; Orbay et aL 1994), in addition, economic impacts can result from restricted international lumber trading. Many trading countries are concerned about importing exotic insect pests and will not accept ambrosia beetle damaged timber in any grade of export lumber. Forest companies sustain financial losses when infested lumber becomes downgraded or rejected from specific markets and shipments of milled products are quarantined or even rejected (Shore 1985). The importance of the forest land base to the economic integrity of B.C. and indeed Canada has been well established. The forest land-base in B.C. covers an estimated 95 million hectares, of which 43.3 million hectares are capable of commercial timber production. In 1990, the Forest Resources Commission estimated that the forest base of B.C. accounts for 18% of the total employment and 24% of the Gross Domestic Product (Anon. 1990). The old growth forests native to coastal B.C. are highly productive and contain some of the highest value trees in Canada. There is no question as to the importance of these forests to the economy of B.C and Canada. The Council of Forest Industries (Anon. 1993a) reported Statistics Canada figures which indicated that B.C. softwood lumber production in 1993 was 14.3 billion board feet. In terms of international trading and import/export of softwood lumber products and marketing, Japan has become the most important trading partner in coastal wood products. A total of 90% of the softwood exports to Japan come from coastal forests, and approximately 90%  4 of all softwood exports are comprised of species that are susceptible to attack (Anon. 1993a). In 1992 Japan imported 4.6 million cubic metres of B.C. softwood lumber. Import figures for 1993 show that Japanese imports of B.C. softwood lumber had increased by almost 15% to 5.4 million cubic metres (Anon. 1994). The export value of lumber fluctuates with world markets and largely depends on species and product. The clear, tight grained lumber cut from the outer portion of these old growth logs ranges from $909/Mibm ($Can) for grade #3 Hemlock 30 cm square x 6 m lumber to high grade #1 Hemlock 10.5 cm squares which can reach a value of $1,953/Mfbm on the Japanese market (Anon. 1994). As logging practices are challenged, forest companies face increasing costs to ensure that their operations comply with the strict environmental and regulatory standards set out within the guidelines of the Forest Practices Code (Anon. 1993b).  With the increased cost of logging  operations it is important that the maximum value return is achieved from all softwood fibre products; thus the forest industry and the ambrosia beetles are in competition for the same high value resource. This insect is accountable for serious economic losses to the B.C. economy. All economic benefits of improved forest management practices are lost if some of the annual losses in the market value of wood products is not recaptured. Log quality must be maintained from the forest to the sawmill to ensure that efforts to improve log inventory control and technological advances in milling efficiency are not wasted. There is a need to modify existing log handling practices to develop an integrated pest management strategy to control this insect pest and reduce the economic impact on the B.C. forest industry. In 1990, the University of British Columbia in collaboration with MacMillan Bloedel Ltd and Phero Tech Inc., embarked on a large scale project to survey the incidence of ambrosia beetles in logs throughout the transportation system around coastal B.C. The 1990-92 Ambrosia Beetle Task Force (ABTF) sawmill survey quantified degrade losses occurring in the value of the major log grades as a result of inventory flow and current storage practices. In 1992, on the Vancouver log market, high grade Douglas-fir and ‘hembal” sorts comprising hemlock and true firs, sawlog  5 prices could fetch $272/rn 3 and $137/rn 3 respectively.  However, degrade as a result of T  lineatum infestation results in the loss of deep clear potential in these high grade sawlogs and value losses increased 57% in comparison to unattacked log value. This represented a loss of 3 for fir and $67.82/rn $77.40/rn 3 for hemlock (Orbay et a!. 1994). Earlier degrade estimates by McLean (1985) were in the region of $63.7 million per annum, however the ABTF survey confirmed losses for MacMillan Bloedel Ltd., of $11 million in 1992, which suggests losses in the region of $120 million per annum for the whole of the coastal forest industry (McLean 1992). Current harvesting practice in coastal B.C. requires that stands are harvested as scheduled within the guidelines of the management plan. However, some log inventory remains on the ground in the forest for some time before it is removed and transported to the mills (McIntosh et aL 1991). For example, trees cut during construction of access roads to newly scheduled harvest sites are sometimes left in the forest and removed with logs which are harvested when the site is active. This wood is sometimes referred to as “right-of-way” wood (McLean and Stokkink 1988). In addition, some harvest settings are not accessible for log yarding and removal prior to the spring flight by ambrosia beetles. Winter storms can create pockets of blow-down trees in locations where no access roads exist. This wood might remain on the ground until stands nearby are scheduled for harvest, and certainly as long as it takes to build the access road. Susceptible logs in these locations can be heavily attacked by ambrosia beetles. Consequently, ambrosia beetle populations can rapidly build up in the forest prior to transportation into storage and processing areas. McLean (1992) found that over 75% of attacked logs encountered during the ABTF survey had been attacked in the forest settings before transportation. Log inventories can quickly accumulate in forest settings, booming grounds and storage areas prior to processing. Borden (1988) suggested that populations of beetles originating in forest harvest and salvage settings are subsequently transported into storage and timber processing areas such as dry land sorts. When infested logs are transported and stored in industrial sorting and storage areas, these areas can become contaminated by beetles as they egress the logs in the late summer and fly to  6 overwintering sites in the forest margins which typically surround these industrial areas. Consequently large populations are maintained in these areas. In the spring of the following year, these individuals will become the attacking mass flight. The purpose of this study is to improve existing integrated pest management systems currently used to protect log inventory in industrial storage and sorting areas. The objective is to improve systems designed to protect stored inventory from attack, by targeting management of ambrosia beetle populations in and around storage and industrial areas. Specifically, this could be achieved through: 1. Improving existing semiochemical-based ambrosia beetle suppression systems through identifying potential areas of high beetle populations, and to focus monitoring and mass trapping; 2. Refining the existing life stage index by McIntosh and McLean (1992) by calculating the threshold temperature for T lineatum development.  A temperature-based model can be  developed to predict time of sister flight beetle log egress. In this chapter, a literature review of the basic biology and ecology of this insect is presented. A major emphasis is to elucidate the host-insect interaction and the role of this interaction in the development of past and present management strategies.  1.2.  Literature Review.  In mid-April when daily temperatures first exceed 16 °C T lineatum flies from overwintering sites in the forest floor and seek out suitable host material. T lineatum is attracted to suitable logs by host odours such as ethanol and ct-pinene (Bauer and Vité 1975). The clear outer portion  7 of the wood becomes stained when the insect inoculates the wood with a symbiotic dark staining fungus upon penetration and subsequent gallery formation (McIntosh and McLean 1992). In order to manage forest pest insects it is important that the biology, ecology and behaviour of the target pest are well understood so that management options can be modified to minimize damage by that pest. 1.2.1. Host Selection Criteria. T lineatum requires highly specific environmental conditions in the host material before it is suitable to attack. Harvest settings provide an abundance of potential host material and if logs are susceptible they will be attacked. Extensive research suggests that it is critical that logs have sustained a period of aging before they are suitable for brood development and should be at least 3 months old before they will be attacked (Prebble and Graham 1957; Dyer and Chapman 1965).  After logs are cut, biochemical reactions in the wood generate highly specific blends of host volatiles.  Over time, arrested translocation of metabolites within the tree, results in oxygen  deficiency which creates an anaerobic metabolic environment. The transition from an oxidative to a fermentative process results in an increase in ethanol concentrations within the wood (Graham 1968). The release of ethanol serves to provide a stimulus to adult ambrosia beetles which are dispersing in the spring (Moeck 1970; 1971), and in combination with other host monoterpenes, such as x-pinene, comprises the major kairomonal cue attracting pioneer ambrosia beetles to the host (Nijholt and Schonherr 1976). Nijholt (1973) found that using turpentine  -  a mixture of  monoterpenes as an antiaggregant, T lineatum attacks could be deterred. Based on this finding, Borden (1988) suggested that high levels of volatiles found in fresh woody material must diffuse to acceptable levels before T lineatum attack will occur.  There is a critical period of time  between felling date and mass attack, which determines susceptibility of the log. Susceptibility of host material to attack is related to the increased accumulation of ethanol as described by Graham (1968), and changes in log moisture content (Kinghorn 1956; Chararas 1961).  8 Prebble and Graham (1957) conducted preliminary investigations into the susceptibility of logs to attack, and the intensity of attack by T lineatum in relation to felling date. Further studies by Dyer and Chapman (1963) suggest that logs from trees felled between August and January were most susceptible to attack, while logs cut in early spring were not attacked. Continued studies by Dyer and Chapman (1965) in a 57 year-old stand of Douglas-fir confirmed the critical felling period to be between January and February. There is evidently some variation in felling period which results in maximum susceptibility and there is also strong evidence of variability between species.  In Norway,  Christiansen and Saether (1968) conducted studies on Norway spruce  (Picea abies (L.) Karst.). Their results supported the premise that logs cut from October to March were most susceptible to attack, and that logs felled later than February are seldom attacked. However, they also claim that infestations were greatest in logs cut in the earlier part of the period. This hypothesis is supported by Chapman and Dyer (1969) in old growth Douglas-fir and although Daust (1985) clearly showed that logs cut throughout the previous year are attacked, logs cut between September and February were most susceptible to attack. In a forest ecosystem without human intervention, the availability of suitable host material is relatively limited, and serves as a regulatory constraint on populations. Over time the three major species of ambrosia beetle, T lineatum and both Gnathotrichus spp. have evolved mechanisms to maximize the use of a relatively scarce resource. T lineatum fly earlier in the year than their major competitors Gnathotrichus spp. and are thus able to locate and infest host material first. One of the key mechanisms which enables ambrosia beetles to exploit their host is the phenomenon of “secondary attraction” which occurs in response to aggregation pheromones emitted from the beetles in conjunction with kairomonal host volatile compounds (Borden 1988). Borden and Slater (1969) reported that the compound responsible for initiating the aggregation response in T lineatum, is synthesized in the hindgut region of the females. The aggregation pheromone of T lineatum was elucidated through isolation of compounds from the frass of females.  It has been described as the tn-cyclic ketal (3,3,7-trimethyl-2,9-dioxatricyclo  9 [3.3.1.0.4,7] nonane) and the compound has been named lineatin. (MacConnell et aL 1977; Borden eta!. 1979). 1.2.2. Life Cycle of the Striped Ambrosia Beetle. The life cycle of the striped ambrosia beetle has been studied extensively (Hadorn 1933; Nijholt 1978; McIntosh and McLean 1992). Its life-history involves an intricate interaction between host, insect and the symbiotic interspecific relationship with ambrosial fungi. Although this insect is thought to be univoltine (Nijholt 1978), there are many complex and ecologically significant changes occurring which initiate and link specific activities and behaviours throughout the life cycle.  Several factors influence the life history of T lineatum, including selection of  overwintering sites, beetle physiology, mass flight and dispersal, brood development and intraspecific communication and behaviour. A generalized schematic diagram of the life cycle can be seen in Figure 1-1 and in the following sections a detailed account of these different components is presented.  Overwintering. Many scolytid beetles overwinter in brood galleries inside their host trees or logs, however, T lineatum seeks overwintering sites outside their host log (Kinghorn and Chapman 1959). Hadorn (1933) was one of the first to discover that teneral (brood) adults leave the host log during the late summer flight to overwinter in the forest litter, overwintering at most 30 m from their breeding place and in dense young forests mostly within 6-15 m from the forest margin. Kinghorn and Chapman (1959) demonstrated that T lineatum overwinter in the top 6 cm of the litter layer, mostly in the top 1.25 cm. Overwintering occurs predominantly within 0.9 m of the base of trees (Dyer and Kinghorn 1961). In addition to locations in the forest floor, adults have been found overwintering in outer bark of standing living and dead trees (Kinghorn and Dyer 1960).  10  MASS ATTACK  4  AD U LTS EGGS  7  TENERALADULTS  SSTER FLGHT d 2rnriA duit)  (pirMB  Figure 1-1. Generalized life cycle of the striped ambrosia beetle Trypodendron lineatum.  Chapman (1956) proposed that T lineatum overwinter very close to their breeding place because teneral adults are unable to fly far.  According to Dyer and Kinghorn (1961),  overwintering may occur up to a distance of 150 m from the stand margin, although the preferred overwintering sites are in locations of lowest incident light near the open forest edge. However, more recent studies of T lineatum dispersal have been conducted by McLean and Salom (1989). Using mass and survey trapping techniques, they found large numbers of T  11 lineatum in old growth forest up to 1.5 km away from nearest right of way. They hypothesize  that these beetles were blown into the area the previous summer and that the rights-of-way provided avenues along which to disperse. They concluded that ambrosia beetles are able to disperse widely in old growth stands and in valleys where active logging is undertaken.  Chapman (1958) proposed physiological reasons to account for restricted late summer flight dispersal capabilities of brood adults in search of overwintering sites. Flight muscles in brood adults are not completely developed, and flight muscles in parental adults degenerate while inside the galleries. Temporary, but distinct, deterioration of flight muscles occur through lack of use and physical restraint inside the gallery. Subsequently prior to egress, adults must feed intensively within galleries to build up reserves to fuel the regeneration of flight muscles. However, if T lineatum are able to sustain flight activity for a period of 20 minutes upon log egress they could be carried some distance. For example, in even a modest windspeed of 15 km/hour they could be dispersed a distance of 5 km.  Borden and Fockler (1973) investigated emergence and orientation behaviour of brood adults. They determined that variable brood maturation rates and environmental temperature influenced sporadic brood egress from the log. Brood beetles showed an initial photopositive response and flew upward to about 15 m. This response reverses when they enter the forest; they fly closer to the ground to locate moist overwintering sites.  T lineatum leaving logs in late summer do not respond to pheromones and consequently are  not vulnerable to mass-trapping efforts using pheromone-baited traps (Borden 1988). Fockler and Borden (1972) found that brood adults are not reproductively mature when they leave the log and rarely mate. Mating activity in revived overwintering individuals increases with time, reaching an active period in February a few months prior to the spring flight. Results suggest -  that T lineatum must undergo a period of reproductive diapause.  12  Pioneer Flight. Initial flight is highly variable and, depending on mean daily temperatures, can occur between March and early May. When temperatures exceed 16° C, overwintering adults leave the forest floor and disperse in search of suitable host material in which to produce their brood (Prebble  and Graham 1957; Nijholt, 1978; Chapman and Nijholt 1980; McIntosh and McLean 1992). At the time of the spring flight, the beetles have metabolized about 50% of their body fat. About 25% of their body fat reserves have been used in overwintering, while a further 25% is used in flight (Nijholt 1967). The beetles are unable to continue feeding until galleries are constructed and fresh crops of ambrosial fungus are grown, therefore, the task of mating and gallery construction must be conducted with less than 50% of the beetles energy reserves (Nijholt 1969).  This would suggest that there is great ecological pressure to leave their  overwintering sites and locate suitable mates and host material very quickly.  Pioneering beetles are the first to respond to kairomonal semiochemicals emitted by host material. In T lineatum the females are the pioneering sex, whereas in some other ambrosia beetle species, for example Gnathotrichus spp., the males are the pioneer sex (Nijholt 1978). The female pioneers will test the log and bore in a short distance. If the host material is suitable, they emit the aggregation pheromone lineatin to initiate the “mass” attack by both males and females.  Flight Dispersal. The flight habits of ambrosia beetles are an important part of their biology. The adults fly in the spring once temperatures exceed 16°C when they are seeking suitable host material, or in  mid to late summer when they are leaving logs in search of overwintering sites  13 (Chapman and Kinghorn 1958). It is important to determine the timing of flight dispersal, so that effective management of populations and protection of logs can be implemented. Knowledge of patterns of insect dispersal provides the key to implementation of pest management strategies.  The importance of flight in T lineatum has been investigated extensively. Graham (1959) found that when beetles break diapause in the spring they leave their overwintering sites in response to strong photopositive stimuli. Strong attraction to light masks the beetles ability to react to olfactory stimuli emitted from potential host material. beetles become indifferent to light or photonegative.  However, flight exercised  This suggests that flight-exercise is  important to the host-finding ability of emerging ambrosia beetles. Balfour and Paramonov (1962) tested the physiological significance of flight by rearing brood insects in the laboratory and placing them in a cage where flight activity was totally restricted. The results of this work showed that flight may not be necessary to the initiation of gallery construction, however, no brood were developed.  Further studies of photic behaviour conducted by Graham (1961)  showed that accumulation of gas in the proventriculus due to flight exercise resulted in a photic reversal resulting in increased response to semiochemicals. Later studies by Bennett and Borden (1971) supported this hypothesis by showing that before an arrestment response to female frass could occur, male T lineatum needed at least 30 minutes of flight exercise.  T lineatum follow distinct diurnal and seasonal patterns of flight and dispersal, which are greatly influenced by environmental factors, in particular, temperature, wind and time of day (Rudinsky and Daterman 1964). Chapman and Kinghorn (1958) studied the seasonal flight activity of T lineatum as a result of site and weather conditions over a three year period. They observed that “swarming” flight activity occurred in the early spring when weather changed from cool and cloudy to warm and sunny weather, and occurred during daylight hours. Their  14 data also suggest that flight activity declines with rainfall. During this three year study, they made observations of T lineatum “...flying against the wind, even to the extent of losing ground during stronger gusts...”, and fI.irther mentioned “...a conspicuous late afternoon down wind flight away from a large number of attractive logs...”.  It is now believed that this  downwind “flight” results from passive dispersal of flying insects, rather than an active phenomenon of directed flight (Salom and McLean 1989).  The dynamics of beetle dispersal in response to various environmental stimuli as determined by wind direction (Salom and McLean 1989), wind speed (Salom and McLean 1990a), and environmental influences (Salom and McLean; 1991) has been thoroughly investigated. Salom  and McLean (1989) evaluated the influence of wind on dispersal in an even-aged second growth forest.  Lindgren® multiple fttnnel traps, baited with lineatin, were stationed in  concentric circles at distances varying from 5 m to 200 m from a central release point. Using the mark-recapture technique, they determined that T lineatum exhibited a strong upwind response to semiochemicals at close range (5 m), with trends up to 25 m. However in the long range (500 m) traps, the trend was downwind, and they concluded that beetles flying that distance were flying with the wind.  Further studies by Salom and McLean (1990b) were conducted under controlled laboratory conditions to determine the flight and landing behaviour in response to semiochemicals at different wind speeds. They concluded that different flight patterns for orienting toward and landing on host material may occur in the presence or absence of winds. They found there was no difference between males and females trapped at windspeeds ranging from 0-0.9 rn/sec. Most beetles were trapped at zero windspeed and trap catches decreased linearly with increasing windspeed. Greater numbers of insects were arrested by semiochemicals under calm conditions.  15 T lineatum dispersal is summarized by Salom and McLean (1991). They concluded that, in the absence of close range attractants, T lineatum tend to fly down wind in search of host material and mates. Forest cover is preferred over open areas. T lineatum are able to disperse up to 1.9 km within the forest where light wind speeds are characteristic as opposed to in the open where winds are more turbulent. An understanding of population dispersal patterns in terms of distance and direction is critical so that effective pest management strategies can be developed.  Brood Production. It has been suggested that mating can occur in the forest floor prior to the spring flight (Fockler and Borden 1972), however mating predominantly takes place on the surface of the log near the entrance hole. After mating, brood galleries are constructed. The male follows the female into the entrance gallery, where the male and female remain as a pair. Both parents work together in brood gallery construction and in tending the brood which develops in galleries inside the log. The female predominantly bores out the gallery while the male keeps the gallery clear of boring dust by pushing it out of the tunnel with its shovel-like modified anterior portion of the head (Figure 1-2). It is these piles of fine white boring dust that is clearly visible on the outside of the log and indicates the presence of an attack. First, an entrance gallery measuring about 1.75 mm in diameter, is constructed in the outer sapwood of the log running in a radial plane towards the centre of the log. At a depth of about 20 mm (ranging from 20 mm to 58 mm) the gallery forks abruptly into lateral egg galleries. These lateral egg galleries run in a tangential plane through the early (or spring wood) between the annual growth rings.  It is along these galleries that the female incises the egg niches  approximately 0.5 mm deep on both sides of the egg gallery and running with the grain of the wood (Figure 1-3).  16 A)  B)  Figure 1-2 Scanning electron micrographs (50x) showing the phenological differences in head structure between: A) male; and B) female 1 lineatum (Scanning Electron Microscopy by J.M. Melluish).  17  Figure 1-3. Typical T lineatum gallery in sapwood of western hemlock Tsuga heterophylla. Notice the geometry of the entrance gallery and the egg galleries branching between the annual growth rings (1 .5x).  The ambrosia beetle relies on symbiotic ambrosial fungi to enable it to exploit the environment in the sapwood of logs and dying trees (Borden 1988). As it enters the wood of potential host material, it inoculates the walls of the gallery at a number of locations with spores of ambrosial fungi.  This activity is thought to be controlled rather than passive  inoculation through burrowing (Farris and Chapman 1957). There is some contention as to which symbiotic fungal species is used by T lineatum. Since ambrosia beetle and some species use more than one of ambrosia fungus (Funk 1970). Funk (1965) identified the symbiotic fungus of T lineaturn in B.C. as Monilia ferruginea (Mathiesen-Kaärik), however Batra (1967) conducted a taxonomic revision of the ambrosial fungi and suggested that the name of the symbiotic fungus should be changed from Monilia ferruginea to Ambrosiellaferruginea.  18 Preliminary studies on the interaction between the fungus and the beetle were undertaken in Germany by Francke-Grosmann (1956a, 1956b).  specialized structures called mycangia.  Spores of the fungus are transported in  The fungi are stored in the mycangia during the  overwintering phase and disseminated in the duff during the spring (Batra 1963).  In  Gnathotrichus spp, the spores are distributed only by males, which carry spores in forecoxal cavities which are located in the prothoracic cuticle (Farris 1963; Schneider and Rudinsky 1969). The ambrosial fungus is not a wood destroying fungus, and thus does not derive nutrition from the disintegration of wood cell walls. In contrast to wood destroying fungi, the ambrosia fungus is a wood-staining organism. Fungal mycelia of this group of fungi penetrate the wood through the pits and cell walls and derive their energy from materials stored within cell cavities (Panshin and De-Zeeuw 1977).  The fungus utilizes starch, sugars and other nutritional  substances present in the cell lumen (Chapman et aL 1963). All that is required for adequate growth, is favourable temperature, oxygen, adequate moisture, and presence of suitable food (Panshin and De-Zeeuw 1977), all of which must be available in suitable host material used by the ambrosia beetle. Moisture content of the host material is critical to the survival of both fungus and brood. Both fungus and brood are only able to survive in green moist wood (Bletchley and White 1962).  Studies by McLean and Borden (1977a) on ambrosia beetle  infestations in sawn lumber showed the optimum moisture content for Gnathotrichus sulcatus survival is between 46.6% and 62.3%.  No attacks were found in wood where moisture  content was lower than 26%. The gallery provides space for the growth of fungal coremia which support droplets of conidiospores (fruiting bodies). Since ambrosia beetles are unable to digest wood, the fungus plays an integral and vital part in the ecology of the ambrosia beetle and provides the beetle its source of nourishment (Borden 1988).  It is these fruiting bodies, which extend into the  galleries, that provide the food source for ambrosia beetles and their larvae (Figure 1-4).  19  Figure 1-4. Photomicrograph (50x) of the ambrosial fungus growth from the gallery walls into the gallery opening. Note the coremia supporting droplets of conidiospores.  Oviposition occurs within 2 weeks of gallery initiation (McIntosh and McLean 1992). The eggs are laid inside the niches along each side of the egg gallery, and are sealed in with a protective barrier of packed boring dust (Figure 1-5A). Eggs hatch 8-10 days after being laid, and the white legless first instar larvae start to elongate the egg niche parallel to the gallery.  There are  conflicting opinions concerning larval development, however the most recent work suggests that there are only 2 larval instars.  Balfour (1962) conducted head capsule measurements and  confirmed that T lineatum went through two larval instars. His results supported work by Novak (1960), but were not in agreement with early work by Hadorn (1933) who proposed that there were four larval instars. In my study, larvae were collected throughout the summer. The results  A)  20  B)  Figure 1-5. Life stage development of T lineatum. A) shows the white packing dust sealing the eggs in to the egg niches (40x); B) shows Li and L2 instar larvae (3 5x) in their larval niches.  21 of head capsule measurement support the claims of Novak (1960) and Balfour (1962) that there are only two larval instars. A detailed account of this can be seen in Chapter 3. When the niche containing the first instar larva has been enlarged, the larva starts to elongate the niche perpendicular to the egg gallery (Figure 1-5B). Parent beetles keep the egg gallery clear by cropping the ambrosial fungus and removing from the gallery the by-products of larval activity which comprise wood fibre from niche excavation mixed with larval faeces.  The developing  larvae eject this material through a hole in the packing dust at the base of the niche in the form of a “fecal strand” (Figure 1-6). Signs of active brood development become apparent on the outside of the log when wood dust piles on the log surface change from white to dark grey-brown. Larval development takes from 3-6 weeks, after which the second instar larvae turn around in the niche and pupate (Figure 1-7A).  Figure 1-6. Second instar larva in larval niche (40x). Note the fecal strand reaching into the egg gallery.  22 A)  •  ..  -  .4;  B)  1, 4  !I  :i.u: 4’  Figure 1-7. Late stages of development in T lineatum. A) shows pupae in their niches (35x); and B) shows two teneral adults in their niches (25x). Note the Parental adult in the egg gallery.  23 After a short pupation of between 8-10 days, adult eclosion occurs. The “teneral” or brood adult remains inside the niche until the exoskeleton is scierotized (Figure 1 -7B), then chews through the packing at the base of the niche and enters the egg gallery. It then turns around and re-enters the niche to feed on ambrosia fungus which line the walls of the niches and deepen the niche by ingesting the softened “fungus-digested” wood fibres.  At this time the teneral adults go through the process of maturation feeding, moving around freely inside the egg gallery and niches. After 2-3 weeks, the brood and parental adults leave the log through the entrance gallery. Both parental and teneral adults egress the log at the  same time, commonly during June/July, and fly to hibernation sites within adjacent forest margins (McIntosh and McLean 1992; Lam and McLean 1992). The rate of development can be highly variable and depends on climatic conditions. Brood development can be completed in 6-10 weeks (Nijholt 1978) but can sometimes require up to 15 weeks (McIntosh and McLean 1992).  1.2.2. Flight Response.  There are three main semiochemicals which have been identified as attractants for the ambrosia beetle: a mixture of host monoterpenes comprising ethanol (Moeck, 1970, 1971) and cx-pinene (Nijholt and Schonherr 1976), and the aggregation pheromone lineatin (MacConnell et a!. 1977; Borden et a!. 1979). These semiochemicals together make up the existing trap bait components used in the Lindgren® multiple funnel trap (Lindgren 1983) frequently used in mass trapping and protective barrier trapping strategies in the industrial setting. Seasonal trapping patterns typically comprise two main peaks: the first and major activity peak is referred to as the “mass flight” and occurs in Spring commonly during the month of April. Adult -  beetles flying at this time are those individuals which left the logs as brood adults the preceding year and have sustained a period of overwintering diapause in the forest floor. When these beetles  24 emerge in the spring they are pheromone-responsive because they have endured the required sexual maturation period during overwintering. Since they are able to respond to aggregation pheromones, they are quickly attracted to the baited traps.  The second or mid-summer flight, which is referred to as the “sister flight”, commonly occurs in late June. It has been hypothesized by Shore et a!. (1987) that the “sister” flight is comprised of pheromone-responsive individuals which have previously attacked unsuitable host material, were unsuccessful in constructing a brood gallery have flown a second time to seek suitable host material. However, it has since been determined that the “sister flight” coincides with the time that parental and brood adults egress the host logs (McIntosh and McLean 1992). Recent studies by McIntosh and McLean (1992) and Lam and McLean (1992) clearly show that the peak of this second flight is synchronous with mid-summer log egress. This suggests that the second peak trap catch is comprised of pheromone-responsive parental adults which have already completed brood rearing that year and are leaving the logs and dispersing. 1.2.3. Management and Control.  Knowledge of the life history, behaviour patterns and host dependence, leaves T lineatum vulnerable to a number of management and control strategies. Borden (1988) identified three key approaches to minimizing damage. The first is to manipulate the host-dependence of T lineatum through reduction of available habitat. This strategy requires regulation in the amount of host material in the form of slash or logs available for brood production. In addition, host material can be actively protected from attack using chemical insecticides or deterrent action such as watermisting.  The second approach proposed by Borden (1988) is to exploit the predictable host-seeking behaviour exhibited by T lineatum. Populations of beetles are attracted to their host through response to semiochemicals  -  specifically host kairomones in conjunction with emissions of  25  aggregation pheromones.  Thus use of aggregation pheromones provides an opportunity for  population reduction through mass trapping, either through the use of trap logs (Lindgren et a!. 1983) or pheromone traps (McLean et at. 1987; Lindgren 1990). The third approach is through the management of overwintering populations in and around dry land sorting and storage areas.  This approach focuses on attempts to reduce suitable  overwintering sites adjacent to industrial areas. Considerable research effort has focused on the development of control and management strategies aimed at minimizing the impact of this pest (Table 1-1). Throughout history, control measures have been varied and extensive. Some of the earliest control measures during the late 1800’s, recommended that trees should be girdled prior to harvest, such that tree stems would be too dry to allow for successful brood development (Hartig 1872).  Even in these early days  sanitary woods operations were advocated (Richter 1918). Through time, much of the effort to manage forest inventories and control the impact of ambrosia beetles has focused on a direct remedial approach. Control methods relied strongly on direct action using chemical insecticides. The era of chemical control began in the 1940’s with the use of highly effective inorganic arsenical compounds with long residual toxicity (Speight and Wainhouse 1989).  During the 1950’s and 1960’s, chlorinated hydrocarbons such as  dichlorodephenyltrichloroethane (DDT), benzene hexachloride (BHC) and Lindane were used operationally in spray operations over booms using rafts, helicopters and hand-held hoses (Richmond 1986). However BHC was found to be highly toxic to fish and pest managers quickly recognized the need for a better mode of boom protection. In 1968, BHC was replaced with the organophosphate methyl trithion which was apparently not injurious to fish (Richmond 1986), although this group contains some of the most toxic chemicals known (Miller and Craig 1980) and many are particularly toxic to vertebrates (Coulson and Witter 1984). In 1970, as a result of political pressure fueled by public concerns over the environmental impact of residual toxicity of  26 Table 1-1. Historical review of strategies explored to control T lineatum (based on Nijholt 1979). Author and Date  Management Methods Researched  Hartig, T. 1872.  Suggested girdling trees prior to felling would prevent beetle attack through drying out the stems.  Richter, H. 1918.  Recommended stump removal, debarking and general clean woods management.  Farky, 0. 1931.  Chemical treatment with Carbolinium 5-10%. Warned against spread of insects due to residual materials left in the woods.  Hopping, G.R. and J.H Jenkins. 1933.  Use of kiln drying.  Hadorn, C. 1933.  Debark trees after falling. Chemically treat trees felled between November and February with Carboleum.  Hadorn, C. 1934.  Debark March-October; Recommended trees felled between November and February should be treated with Carboleum; burn or spray top layer of debris at storage sites.  Enzinger, F. 1949.  Chemical control using DDT.  Graham, K. and W. Webb. 1952.  Chemical control. Preliminary report on use of benzene hexachioride (BHC) applied as a spray on water-stored booms.  Graham, K. 1953.  Found logs treated with BHC were unaccountably heavily attacked.  Graham, K. 1954  Tested use of chemical control. Explored chemical attraction by logs.  Dominik, J. 1956  Tested feasibility of chemical control of insects inside wood using DDT and BHC.  Kinghorn, J. 1955  Preventive chemical control strategy using Lindane.  McMullan, D. 1956  Economic impact of reducing log inventories during spring and summer.  SchOnherr, J. 1958  Experimented with steam treatment.  Novak, V. 1960  Protective and defensive strategies using natural enemies and diseases, forest and stockyard sanitation, also chemical treatment of soil and logs using BHC. Continued  27  Table 1-1. Continued. Author and Date  Management Methods Researched  Kinghorn, J. 1960  Chemical control using Lindane and Thiodan. Due to toxicity of Thiodan to fish and mammals, recommended that testing be conducted prior to use on water-stored log booms.  Richmond, H. 1961  Chemical sprayed log booms using helicopter.  Richmond, H. 1962  Bundled logs loaded on train flat-bed wagons were treated with BHC.  Balfour, R. and R. Kirkland 1962  Effects of creosote treatments on ambrosia beetle populations breeding in stumps.  Bletchley, J. and M. White 1962  Overview of ambrosia beetles in Scotland. Recommended inventory reduction and chemical treatment using BHC.  Novak, V. 1962  Soil treatment under storage areas and spray logs with chemical insecticide, in conjunction with sanitary woods management.  Johnson, N. 1964  Different drying rates of felled trees with and without tops (trees dried faster when crowns left attached).  Rummukainen, U. 1964  Experiments with DDT in Norway to prevent attack by scolytid beetles.  Schwerdtfeger, F. 1964  Concentrations, dosages and costs of preventive chemical spraying.  Richmond, H. 1966  Summary of 30 years of use of chemicals to control ambrosia beetles.  Finegan, R. 1967  Warned about environmental contamination using BHC. residues found in oysters, fish and birds.  Reisch, J. 1967  Recommended debarking also treatment of logs with BHC. and DDT.  Schindler, U. 1967  Preventive measures including immediate removal of logs, Chemical spraying of BHC. mixed with fuel oil.  Schindler, U. 1968a  Used BHC. fuel-oil and DDT mixtures to control population growth due to windfalls in Germany in 1962.  Schindler, U. 1 968b  Recommended “clean” woods management in addition to chemical control.  -  Continued  28 Table 1-1. Continued Author and Date  Management Methods Researched  Nigham, P. 1969  Evaluated 12 different chemical insecticides. All 12 tested more toxic than BHC.  Richmond, H. 1969  Chemicals help to control, but changes in woods management best strategy.  Hedlin, A. and T. Woods 1970  Tested preventive treatment of Douglas-fir with chemical sprays of BHC and methyl/trithion.  Schindler, U. 1970  Chemical trials using combinations of Lindane and Carbamate in water effectively killed beetles up to 4-5 cm inside the wood.  Moeck, H. 1970  Tested Ethanol as primary attractant for Ambrosia beetles.  Richmond, H. and W. Nijholt 1972  Biological assessment of effects of watermisting system used to protect dry land sorted logs. Concluded watermisting effective and practical method of protection.  Nijholt, W. 1973  Logs treated with turpentine oil as antiaggregant provided short-term protection.  McLean, J.A. and J.H. Borden 1975  Conducted surveys in a commercial sawmill setting using pheromones.  MacConnell et aL 1977  Isolation and tentative identification of lineatin as the aggregation pheromone for T lineatum.  McLean, J.A. and J.H. Borden 1 977a  Tested suppression of ambrosia beetles around commercial sawmill using baited traps. First verification of ambrosia beetle attack on freshly sawn lumber. Suggested using aggregation pheromones as bait near fresh slabbing. After infestation, cull slabs could be pulped.  Nijholt, W. 1978  Attributed population buildups as a result of move towards dry land sorting operations.  Overend, M. 1978  Identified increased problems due to increases in dry land sorting. Recommended rapid processing of high value logs, and watermisting.  Lindgren, B.S. 1983  Developed Lindgren® multiple funnel trap. This trap design is now used extensively in mass-trapping programs throughout B.C. Continued  29  Table 1-1. Continued Author and Date  Management Methods Researched  Lindgren, B.S. and J.H. Borden 1983  Survey and mass trapping techniques in four different dry land sorts. Surveyed spatial distribution and determined population estimates of overwintering beetles. Recommended mass-funnel and drainpipe traps may significantly improve trap catches relative to vane trap.  Shore, T. and J.A. McLean 1984  Tested optimum trap height for trapping Ambrosia beetle. Proposed that maximum catches occur at, or just below height of surrounding vegetation.  Shore, T. and J.A. McLean 1985  Used pheromone-baited traps to survey spatial and temporal distribution of ambrosia beetles in a sawmill. Recommended pheromone-based mass-trapping program.  Richmond, H. 1986  Summarized history of chemical control strategies used in B.C. Assessed efficacy of water misting and found continuous watermisting from dawn to dusk provided 100% protection, but costly. Discussed progression to use of semiochemicals.  McLean, J.A., A. Bakke and H. Niemeyer 1987  Evaluated relative efficacy of three different traps and two pheromone lures in Canada, Norway and Germany.  Salom, S. and J.A. McLean 1988  Tested combinations of semiochemicals used in the existing trap-bait. Proposed that lineatin is the only effective trap bait in attracting beetles to the traps.  Shore, T. and J.A. McLean 1984  Use of mark release recapture techniques to evaluate pheromone based mass trapping program in an industrial setting.  Konig, E. 1988  Mass-trapping in forest in Germany to reduce populations in the field.  Prazak, R. 1991  Tested biological control of T lineatum through direct and indirect infection using Beauveria bassiana (Bals.) fungi.  Lam, D.K.W. and J. A. McLean 1992  Pheromone-baited traps used to determine abundance and occurrence of ambrosia beetles in industrial log storage area. Suggested transportation of infested booms and local wind patterns result in increased populations in these areas.  McIntosh, R. L. and J.A. McLean 1992  Insect development index as tool to predict where and when insects will egress logs.  30 chemicals and public health, the use of chemical control was banned; first over fresh water then finally over salt water, after the International Woodworkers of America refused to handle sprayed logs in the Alberni inlet (Richmond 1986). In the post-spray period of the 1970’s and 1980’s, management intervention focused on more environmentally-acceptable methods of protecting inventories in dry land sorts. Control methods developed into a phase of preventive approach, where physical barrier strategies such as watermisting were tested and implemented (Richmond and Nijholt 1972). While this method was effective, it was costly to install and required both a constant supply of water and adequate drainage (Richmond 1986) This method is cost effective when applied to high value sorts and is still implemented in the industrial setting today. In the mid 1970’s rapid advancement in the development of semiochemicals as a pest management tool marked a transition period when semiochemicals were introduced into monitoring and mass trapping programs (McLean and Borden 1975, 1977a, 1979; Lindgren and Borden 1983; Shore and McLean 1984, 1985). In 1977, preliminary trials testing the feasibility of operational suppression strategies using pheromone-based trapping were initiated in a commercial sawmill setting. Mass-trapping studies in an industrial setting by McLean and Borden (1979) marked the first evaluation of the use of semiochemicals as an operationally feasible alternative to chemical control in dry land sorting areas. The use of trapping has further developed, along with changes in management philosophy, and became an integral part of an acceptable integrated pest management approach (Nijholt 1979; Borden 1988; McLean and Stokkink 1988; Lindgren 1990).  Currently, pest management  specialists at Phero Tech Inc., located in Delta B.C., provide a complete operational pest management service conducting mass trapping and population suppression for industrial clients throughout North America.  31  If pest management is to be effective, an integrated approach must be taken.  Management  strategies should incorporate tight inventory control in conjunction with protective measures such as water sprinkling and extensive annual monitoring and mass trapping programs in industrial processing and storage areas.  1.3.  Summary.  Research into strategies to control T lineatum has focused on the behaviour and dispersal characteristics of the attacking spring flight of ambrosia beetles (Dyer and Chapman 1965; Borden 1984; Salom and McLean 1991). Early studies by Kinghorn and Chapman (1959) concentrated on overwintering brood adults. Borden and Fockler (1973) studied the emergence and orientation behaviour of the ambrosia beetle with respect to photic responses. Annila et a!. (1972) conducted studies in Scandinavia on broad-scale seasonal flight and emergence of ambrosia beetle. Lindgren and Borden (1983) assessed populations in timber processing areas with the view of implementing mass trapping control strategies.  Although the biology of insect development has been extensively studied, very little information exists which links development in forest coleopterans to environmental conditions in a predictive manner.  McIntosh and McLean (1992) constructed a life stage development index for T  lineatum.  On the basis of insect development, this index provided managers with a tool to  determine the time and location that logs were attacked by T lineatum. With an estimate of the length of time required for T lineatum to complete development, the time and location of brood beetle egress from logs can be predicted. However this index was based on localized information and can not be reliably used as a predictive model throughout the province. To be more broadly applicable, the index proposed by McIntosh and McLean (1992) needs further development. T lineatum development rates must be standardized through refinement of the existing index to include the effects of temperature variability to develop a temperature-based heat sum model.  32 This index could then be applied in decision support systems to predict brood egress from logs under different climatic conditions throughout coastal B.C.  Economic losses could then be  reduced by minimizing the risk of insect contamination in storage areas.  There is an opportunity to modif’ management and control of populations in and around industrial sorting and storage areas so that stored inventory can be protected from attack. Exiting methods of inventory management could be reviewed and modified to provide protection through manipulation of the biological relationship of T lineatum with its host.  Current  operational mass trapping and population reduction tactics could be focused to improve the efficacy of these management options. Finally, decision support indices could be derived to help managers interpret key points in the T lineatum life cycle and provide them with a basis for management and placement of high value log inventory.  The specific objectives of this thesis to support these aims are:  1. To evaluate response of sister flight beetles to semiochemicals alone and in combination to ensure effective late summer trapping.  2. To determine if there is a correlation between sister flight catches and mass flight catches the following spring.  3. To develop a heat sum based development model of T lineatum.  33 CHAPTER 2. POPULATION MONITORING WITH SEMIOCHEMICALS.  2.1. Introduction.  In chapter 1, a historical perspective of management approaches to control T lineatum was presented in detail. Over time, strategies developed from a clean woods management approach through an era of direct remedial chemical control, into a preventive era of integrated pest management.  Watermisting in conjunction with the application of semiochemicals in mass  trapping and monitoring programs quickly replaced chemical control as the tactics of choice. Tight inventory control in conjunction with annual mass trapping is the current strategy used to control ambrosia beetles in industrial processing and storage areas.  In coastal B.C., log inventories accumulate in forest settings, booming grounds and storage areas prior to processing. Populations of beetles originating in the forest are transported into storage and timber processing areas such as dry land sorts (Borden and McLean 1981; Borden 1988). Large populations of T lineatum are maintained in these areas because brood adults exit infested stored logs and overwinter in the forest margin adjacent to storage and processing areas; thus contaminating them. In the spring of the following year, these individuals will leave the forested margin and become the mass attack. Any susceptible logs held in storage in these areas during the period of ambrosia beetle flight activity could be attacked and infested.  During the 1990-1992 ABTF study the movement of inventory, in particular boom storage practices, was closely monitored. Booms which comprised both unattacked and heavily attacked logs originating in forest settings were brought into the Alberni Inlet for storage. These logs could remain in storage for many months depending on sort and the influence of fluctuating export markets. Some high value or scarce log sorts are stored for months while managers in  34 sorting yards and booming grounds wait for enough volume to accumulate before further transportation.  For example, some high value oversize sawlog sorts are sometimes left to  accumulate before the boom is closed off and barged out to specialty mills on the East coast of the Island such as Chemainus sawmill, or to specialty mills in Vancouver (McIntosh et aL 1991).  Collectively, the five logging divisions of MacMillan Bloedel Ltd (Alberni Region) sustained a degrade loss of $4 million. While much of this loss (approximately 86%) occurred in the forest, some of the damage occurred because logs were left in storage. Thus, logs which had left some logging divisions uninfested, were attacked while stored beside contaminated forest margins along the shores of the Port Alberni Inlet.  Populations in and around contaminated industrial sorting and storage areas are currently monitored and controlled through operational semiochemical-based mass-trapping. Preventive barrier trapping and strategically placed pheromone traps in conjunction with cull trap bundles of lower grade logs are frequently used management strategies for the suppression of local T lineatum populations (Borden and McLean 1981).  There are three main semiochemicals which have been identified as attractants for the ambrosia beetle: a mixture of host monoterpenes comprising ethanol (Moeck, 1970, 1971), the synergistic effect of ethanol with cx-pinene (Nijholt and Schonherr 1976) and the aggregation pheromone lineatin, the tri-cyclic ketal (3,3, 7-trimethyl-2,9-dioxatricyclo [3.3.1.04,7] nonane) (MacConnell et aL 1977; Borden et a!. 1979). The ecological importance of these three semiochemicals was outlined in section 1.4 of Chapter 1. These semiochemicals together make up the existing trap bait components used in the Lindgren® multiple fbnnel trap in mass trapping and protective barrier trapping strategies in the industrial setting.  35 The overall objective of the research presented in this chapter is to explore hypotheses which are related to reducing the impact of T lineatum in industrial dry-land sorting and storage areas. The work is focused on refining ambrosia beetle monitoring methods and to improve population management; specifically to improve deployment of semiochemical-baited traps currently used in monitoring and suppression strategies.  Through manipulation of the existing trap bait  components, late season trapping surveys could be refined and trap counts used to identify high hazard areas. To fulfill the objectives of this study specific biological criteria outlined in Chapter 1 were manipulated. In the first phase, components of the existing trap bait were investigated.  The  second phase tested the relationship between late season trap catches and populations emerging the following spring. Late summer trap numbers might help managers focus barrier and mass trapping efforts employed to intercept the mass attack the following spring.  The following  hypotheses were tested: 1. Lineatin is the only significant trap bait for trapping and monitoring T lineatum sister flight. 2. Sister flight trap catches are correlated with trap catches the following spring.  2.2. Latin Square Test 1992. -  Salom and McLean (1988) investigated the effect of semiochemicals used for trapping T lineatum in the spring. Components of the existing trap-bait were tested individually and in all combinations.  Similarly Liu and McLean (1989) studied the influence of the trap-bait  components, both singly and in combination, for trapping the mass flight of Gnathotrichus sulcatus and G. retusus.  In both of these studies a Latin square design was selected, and  performed in a lineal fashion. The Latin square design is commonly used when the expected  36 variation between experimental units is high. To remove the effects of variation this design requires that treatments are blocked in two directions such that each treatment is replicated in each block equally (Zar 1986). In both studies trapping period and trap position were used as row and column replication parameters. The significance of each component of the existing trap-bait for trapping sister flight T lineatum has not yet been investigated.  In this study, to be consistent with the studies of Salom and  McLean (1988) and Liu and McLean (1989), a similar 8 x 8 Latin square design was selected to evaluate the role of semiochemicals alone and all possible combinations in trapping sister flight T lineatum. For the purposes of this study, the late season is defined as that period after which current year brood beetles are known to be emerging. 2.2.1. The Study Area. In 1992, studies were conducted near Port Alberni which is located in the South Central region of Vancouver Island off the west coast of B.C. The city of Port Alberni is located at the Northern extremity of the Alberni Inlet which runs almost North-South, entering into the Pacific Ocean (Figure 2-1). The area lies in the very wet maritime subzone of the Coastal Western Hemlock (CWH) biogeoclimatic zone of the coast mountain physiographic region of North America. The study area was situated near the China Creek dry land sort operated by MacMillan Bloedel Ltd., located on the eastern side of the Alberni inlet 10 km south of Port Albemi. The Alberni Inlet is bounded by: Longitude 125° 47’ to 125° 50’ East, by Latitude 49° 09’ to 49° 15’ North (Figure 22).  37 WE  0  50  100  ki lometres  Figure 2-1. Geographic location of Port Alberni (Scale 1: 50,000). 2.2.2. Methods and Materials. Eight Lindgren® 12-unit multiple funnel traps were chosen from a line of traps which had been placed along the logging road adjacent and to the North of the China Creek dry land sort (Figure 2-2).  The traps had been positioned by Phero Tech Inc. personnel during commercial mass  trapping operations in 1992. Semiochemical baits and their placement in the traps were consistent with Phero Tech protocol. The lures were: Ethanol (95%) released at a rate of 50-60 mg/24 h from a 20 mL polyvinylchloride (PVC) sheath and suspended down the center of the funnel trap; a-pinene released from a 20 mL plastic bottle at a release rate of 50-80 mg/24 h and suspended from the central funnel; and two slow-release lineatin lures released from PVC “Flexiure” strips at a rate of 50 .tgf24 h (J. Carison, personal communication). These lures were hung from the second funnel from the top and the second funnel from the bottom. Placement of all lures in the traps was consistent with optimum aerodynamic properties to enhance trap efficiency as determined by Lindgren (1983).  38 LEGEND Cr11’ LIMITS ‘  CONTOIJRS40,l PAVED ROADS LOGGING ROADS  IR  INDIAN RESERVE  WE  Figure 2-2. Location of the study area at the China Creek dryland sort near Port Alberni (Scale 1:50,000). This map of the study area was digitized using Terrasoft 9.0 Geographic Information System (GIS) from the Energy Mines and Resources Map of the Alberni Inlet; Map sheet number 92 Ff2, 4 ed., Surveys and Mapping Branch, Dept. Energy Mines and Resources, 1980.  39 The traps were arranged in a lineal array at 20 m spacing along the side of the logging road. Traps were hung such that the collecting cup at the base of the trap was approximately 40 cm. above ground level. The trapping study was run for 7 days between July 24 and July 311992. During this time, traps were monitored daily and the number and sex of insects trapped was  recorded in each treatment. 2.2.3. Experimental design. A 2 factorial experiment in an 8 x 8 Latin square design similar to that used by Liu and McLean (1989) was selected to evaluate mid-summer ambrosia beetle sister flight response to Lindgren® multiple funnel traps unbaited and baited with ethanol, c-pinene and lineatin both individually and in combination. The following hypothesis was tested: : There is no significant difference between treatment means; 0 H : At least one of the treatment means is significantly different (cL 1 H  =  0.05).  Since a 2 factorial experiment was selected, there are eight permutations of the trap bait. The treatments investigated were: Control (CONT), ethanol (E), cx-pinene (P), ethanol (EP), lineatin (L), lineatin  +  ethanol (LE), lineatin  +  cL-pinene (LP) and lineatin  +  +  ct-pinene  ethanol  +  a  pinene (LEP). The row and column categories used in this design were time and trap position. The treatments were blocked by assigning each treatment to each position throughout the eight replicate rows.  The rows and then the columns were randomized thus generating the  treatment/block randomization used in this experiment. The randomization of these treatments can be seen in Appendix 2-1. Time replication was achieved by leaving each randomized array in position until the highest trap catch exceeded 100 insects regardless of the number of days required to reach this number. Then the lineal block was re-randomized to time 2 as defined by the Latin square design. This procedure must then be repeated for each of the eight replications.  40 2.2.4. Results. During the trapping period, extreme fire hazard caused a premature shut down of the China Creek dry land sort prior to completion of the experiment. When the flow of inventory was closed, the source of freshly egressing insects was cut off Consequently, there was a shortage of “local” insects to complete the test. As a result, this experiment was only replicated three times and precluded analysis as a complete Latin square design.  However, a preliminary one-way  analysis of variance was conducted on the three replications to detect data trends. Between July 24-31, a total of 842 T lineatum were trapped in the three completed replicates. Of this total, 319 were males, and the remaining 523 were female, thus the male to female sex ratio was 0,61:1. All four treatments containing the aggregation pheromone lineatin consistently trapped more insects than any treatment lacking this component. The trap catches of females in the four treatments containing lineatin were similar only ranging from 117 to 141, while there was greater variability in the numbers of males trapped ranging from 53 to 108. The greatest catch of both males (108) and females (141) occurred in the lineatin + ethanol treatment (Table 2-1). Table 2-1. Number of male, female and total T lineatum trapped in each treatment in the first three replicates of the 8 x 8 Latin square test at China Creek, July 1992. Treatment  1  Number of Beetles  Total  Male  Female  Control E P EP L LE LP LEP  0 1 0 4 78 108 53 75  0 7 6 7 117 141 127 118  0 8 6 11 195 249 180 193  TOTAL  319  523  842  Mean Total 1 (per Trap) 0.OOa 2.67a 2.00’ 3.67a b 0 • 65 0  83.00k’  b 0 , 60 0  b 3 , 64 3  2 ±5D 0.00 2.31 2.00 2.89 22.27 56.11 4.00 43.66  Means followed by the same letter are not significantly different (P <0.05; Student-Newman Keuls test, [Zar 1984]). 2 Standard deviation.  41  Initial analyses using total trap catch resulted in highly heterogeneous treatment variances. Heteroscedasticity of the data required that the data be transformed, therefore the trap catches were transformed to  Xl  =  10 (x+1) as shown in Table 2-2. Using Systat® statistical software, Log  the analysis of variance was conducted on the transformed data to test the hypothesis that there is no difference in the mean trap catch between treatments. One-way analysis of variance revealed that there was a highly significant treatment effect (Table 2-3). Table 2.2. Transformed mean number of male and female T lineatum trapped at China Creek between July 24-31, 1992. Treatment  Replicates  1 Mean 2 Male  ±  3 SD  2 Female  ±  3 SD  C  3  0.000a  0.000  0.000a  0.000  E  3  O.100a  0.174  O.434a  0.380  P  3  0.000a  0.000  O.392a  0.357  EP  3  0.360a  0.102  0.460a  0.276  L  3  1.4l51  0.143  b 1584  0.157  LE  3  b 1455  b 1624  0.290  LP  3  b 1269  0.402 0.048  b 1635  0.048  LEP  3  1.336’  0.310  b 1556  0.254  1  To maintain homogeneity of variance, data transformed to X’= Log 10 (x+1) before analysis of variance. 2 Means within the same column followed by the same letter are not significantly different (P < 0.05; Student-Newman-Keuls Test [Zar, 19841). 3 Standard deviation Table 2-3. One-way analysis of variance of male and female T lineatum trap catches (transformed X’ Log 10 (x+1) at China Creek, 1992. (n = 3). Source  DF  Male MSE  Between Treatments Error 1  Significant at P  =  Female F-Ratio  7  1.393  34.701  16  0.040  0.065  0.05; F 16 , 7  2.66  MSE 1.462  F-Ratio  22.40  42 2.2.5. Discussion and Conclusions. The hypothesis that there is no significant difference in mean trap catch using different combinations of the existing trap bait cannot be conclusively tested. Because the experiment was interrupted and only three of the eight replicates completed, the integrity of the design has been  lost. However, these data revealed a pattern which suggested that there is no significant gain in trap catch through the addition of ethanol and/or c-pinene, and that lineatin is the only significant trap bait for the sister flight. These preliminary results are consistent with the trap-bait studies conducted by Salom and McLean (1988). To test the significance of trap bait components, both singly and in combination, the experiment was repeated.  The complete randomized array of  treatments were tested again so that a comprehensive analysis of the data could be performed and statistically sound conclusions can be drawn.  2.3. Latin Square Test 1993. -  2.3.1. Study Area. On April 6 1993, prior to the spring flight of T lineatum, a lineal array of 20 semiochemical baited Lindgren® multiple funnel traps (12 unit) were set up to monitor the initiation and progress of the 1993 mass flight. This trap line was established in the forested margin along the Foreshore of the Pacific Spirit Park area which lies between the Point Grey booming grounds at the mouth of the Fraser River and Southwest Marine Drive, Vancouver B.C. spacing and at approximately 1.5 m above ground level.  Traps were hung at 20 m  To ensure maximum trap catch, the  collecting cups were hanging at the height of surrounding vegetation where the most insects are  found (Shore and McLean 1984). From these 20 traps, a block of 8 were selected for use in the trap bait test.  43 2.3.2. Methods and Materials. All eight traps were checked daily between July 6 and August 20 1993. Experimental protocol was the same as the 1992 preliminary study at China Creek.  As in the previous study, each  replicate was run until the best trap catch was equal to or exceeded 100 insects, at which time the traps were emptied, the insects counted and sexed and the traps re-randomized to start the next replication. 2.3.3. Experimental Design. A Latin square design identical to that used in the preliminary study in 1992 was used. All eight possible combinations of the three existing trap bait components including a no bait control were deployed in each time period. Treatments were re-randomized at the end of each trapping period. The randomization pattern for this experiment can be seen in Appendix 2-2.  2.3.4. Results.  During the course of this study, all eight treatments were replicated eight times. Throughout the trapping period, a total of 2,501 adult beetles were trapped. Of these, 1,317 were females and 1,184 were males, a sex ratio of 0.90 males: females. There was a bimodal pattern in numbers of beetles trapped across the eight treatments. Mean trap catch in the ethanol, x-pinene, ethanol -pinene and control treated traps was less than 1 insect per trap.  +  a  However, all treatments  containing the aggregation pheromone lineatin either singly or in combination with other components consistently trapped the most beetles. The highest number of insects (710) were trapped in the lineatin + a-pinene baited trap (Table 2-4).  44 Table 2-4. Numbers of male, female and total T lineatum trapped between July 6 and August 20, 1993 in each of the eight treatments in the Foreshore area of the Pacific Spirit Park, Vancouver B.C. Number of Beetles  Treatment  Mean Total  Male  Female  Total  (per Trap)]  Control  1  0  1  0.125’  1.035  E  4  2  6  0.354  P  0  1  1  0.750’ 0.125a  EP  2  2  4  0.5001  0.756  L  257  263  520  52.394  LE  288  328  616  65.0001) b 77000  42.484  LP  354  356  710  88.75@  39.273  LEP  278  365  643  81.625k’  32.697  1,184  1,317  2,501  Total  0.756  Means followed by the same letter are not significantly different (P <0.05; Student-Newman Keuls test, [Zar 19841. 2  Standard deviation.  A Bartletts test for homogeneity of variance of total trap catch data revealed a significant difference between treatment group variances (F  =  22.01; df = 7,56; P  =  0.000 1). Mean trap  catches in these data are clearly heteroscedastic, thus the assumption that there is homogeneity of variance has been violated. To correct for this, trap catches were transformed as in 1992, using the X’  =  10 (x+1) before analysis of variance. Analysis of variance of the transformed data Log  shows that there is a significant treatment effect and, from the results, it can be concluded that at least one of the treatments is significantly different (Table 2-5). Multiple comparison tests were made using Student-Newman-Keuls multiple range test (P <0.05). Traps baited with ethanol and ct-pinene were not significantly different to the unbaited control.  In addition, there were no  synergistic effects from adding ethanol and ct-pinene either alone or in combination to lineatin (Figure 2-3).  45  2.60  I  I  2.00 +  x  0) 0 -J U) C.)  1.50  a)  (0  0 L.  a)  .  E  1.00  4) 0.60  a  a 0.00 Control  E  P  EP  L  LE  LP  LEP  Figure 2-3. Mean number of T lineaturn trapped in the 8 x 8 Latin square study over a period between July 6 and August 20, 1993. Means labelled with the same letter are not significantly different (SNK; p < 0.05).  46 Table 2-5. Analysis of variance of total male and female T lineatum trap catches in the 8 x 8 Latin square test in Vancouver B.C. (P = 0.05). Source  DF  Time  7  0.072  1.119  0.045  1.230  Position  7  0.045  0.730  0.035  0.938  Treatment  7  4.666  72.552  5.328  144.622  42  0.064  Error 1  Significant at P  =  MSE  0.05; F  7,42  Male  F-Ratio  MSE  Female  F-Ratio  0.037 2.24  =  To determine if there are any interactions or synergistic effects, the treatment sum of squares was broken down into factorial components.  An analysis of variance was run on mean male and  female trap catch data (Table 2-6).  Table 2-6. Analysis of variance of male and female T lineatum trapped in Vancouver B.C. between July 6 and August 20, 1993. Note: data transformed Log 10 (x+1). Source  DF  Time  7  0.072  1.119  0.045  1.230  Position  7  0.045  0.730  0.035  0.938  E  1  0.068  1.053  0.067  L  1  32.382  503.518  37.006  P  1  0.010  0.148  0.129  3.491  ExL  1  0.003  0.045  0.001  0.03 1  ExP  1  0.063  0.987  0.012  0.315  PxL  1  0.105  1.626  0.080  2.180  ExLxP  1  0.03 1  0.485  0.001  0.029  42  0.064  Error 1.  Significant at P  =  MSE  0.05; F  1,42  =  Male  F-Ratio  MSE  0.037 4.09.  Female  F-Ratio  1.832 1004.4751  47 2.3.5. Discussion and Conclusions.  Trapping studies conducted in 1992 and 1993 were designed to test the response of “sister  flight” beetles to each of the semiochemicals currently used in the trap bait. The results of this study clearly demonstrate that lineatin is the only significant trap bait for catching “sister flight” beetles.  There are no synergistic effects from the addition of ethanol and cL-pinene either  individually or in combination with the aggregation pheromone lineatin. However, it is important to notice that trap catches are neither enhanced nor impeded by the addition of these components to lineatin.  Salom and McLean (1988) determined that mass flight trap catches were not  significantly enhanced through the addition of ethanol or x-pinene alone or together to lineatin baited traps. They demonstrated that for the mass spring flight of T lineatum the only significant trap bait in this trapping system is the aggregation pheromone lineatin. The results of the 1992-93 trapping study of sister flight response support the hypothesis proposed by Salom and McLean (1988) that the lineatin bait alone is sufficient for use in operational mass trapping programs. From an ecological perspective, the importance of primary attraction by ethanol and ct-pinene, and the secondary effects of the lineatin may be highly significant in attracting T lineatum to suitable host logs in the forest. These same semiochemicals may also be important when used in trapping devices which require that insects land on the trap and crawl inside before they become trapped (McLean et at. 1987). In B.C., the Lindgren® multiple fi.innel trap is currently used ubiquitously in operational mass trapping programs in the industrial sector. This trap works on the principle that insects attracted to the trap will fly into it and will be re-directed down into the trap via the reverse cone funnels. This trapping mechanism has been referred to as a “passive knockdown” style of trap (Mclean et aL 1988).  However, in a passive trap system these  additional trap bait components are not required and do not improve trap catch. It has also been suggested that the role of primary attractants such as ethanol and x-pinene may not be significant in industrial areas where there is likely and abundance of these volatiles from stored inventory (Salom and McLean 1988). The results of both this study, and that conducted by Salom and  48 McLean (1988) concur that the lineatin bait alone is sufficient for the purpos of mass trapping T lineatum in and around industrial areas where the Lindgren® multiple funnel trap is deployed.  The recommendation to use lineatin alone in mass trapping programs is intended to encourage more economical mass trapping. I strongly recommend that savings made by industrial clients through the potential reduced cost of the trap bait be re-invested into additional lineatin-baited traps, and not withdrawn from mass trapping investment. Similarly, although the exclusion of these components may constitute a potential loss in revenue to the producers of the trap bait there may be significant gains in terms of reduced service time for the pest management consultants and an increase in lineatin-baited traps to be deployed in on-going mass trapping programs.  2.4. Trapping Correlation Study 1993 1994. -  2.4.1. Introduction.  One feasible ambrosia beetle management strategy currently used includes active suppression of beetle populations. Intercepting beetles in flight before they reach their hosts is a common and widely acceptable practice in confined industrial sorting and storage areas (Borden and McLean 1981).  It is this strategy which provides the rationale for suppression and mass trapping  operations currently used. As discussed in section 2.0., beetle populations accumulate in and around confined industrial sites. To manage these populations, and protect log inventory, it is important to have an estimate of the number of beetles in the area and their distribution so that effective mass trapping can be implemented.  Beetles overwintering in the forest floor around dry land sorts can be easily  surveyed (Chapman 1974), however populations are constantly changing because new individuals are brought in to the dry land sort in infested log inventory.  Lindgren and Borden (1983)  conducted spatial distribution and population estimates of overwintering T lineatum by sampling  49  duff and trapping in dry land sorting areas. This method required collecting duff samples on line transects from the base of trees. However, the results indicated that this method is less reliable in areas where the forest margins are not so well defined.  This can easily result in  underestimates of overwintering populations. Lindgren and Borden (1983) determined that this method of estimating populations is unreliable; however, they suggest that when used in conjunction with trap catches, over a number of years, a fairly reliable population index could be achieved. Studies conducted by Salom and McLean (1990b) clearly demonstrate that the number of T lineatum beetles trapped decreased with increasing windspeed, with the highest trap catches occurring under still conditions. Thus T lineatum is dispersed passively on the wind. Dispersing sister flight beetles could be used as an indicator of populations in and around the trap. In the sister flight, parental adults (which are found in the traps) egress the logs at the same time as teneral adults. Both parental and teneral adults are likely to be influenced by the same wind and weather patterns governing dispersal, and direct teneral adults to their overwintering location. It could then be concluded that sister flight beetles would represent some portion of the overwintering population which has arrived in the area of the trap. I hypothesize that there should be a correlation between numbers of parental adults trapped in the sister flight, with the numbers of teneral adults overwintering in the area around the trap. These individuals will comprise the mass spring attack the following year. If a relationship exists, regression equations will provide a quick and easy estimate of populations predicted in any given location simply by using trap catch numbers of sister flight beetles the previous year. The purpose of this experiment is to determine if there is a correlation between the number of ambrosia beetles trapped in the late summer in 1993, and the number of host-seeking ambrosia beetles trapped in the spring mass attack flight in 1994.  50  2.4.2. Spring Mass Flight versus Sister Flight. There are two distinct T lineatum flight peaks which can be detected in trapping programs. The difference between the two populations of ambrosia beetles must be defined and described. The term “mass attack” is used in reference to those beetles which are flying in the spring after overwintering in the forest margin. Beetles flying during the mass attack comprise the previous season’s teneral or brood adults, in addition to any parent beetles that have successfiully overwintered for a second time (Chapman 1958). The term “sister flight” refers to the parent beetles which have produced their brood and leave the log in the late summer along with brood teneral adults. Although I have observed teneral adults in the traps, I consider these as incidental catches of dispersing beetles, since it is thought that the teneral or brood adults are not pheromone responsive and will not be detected in the pheromone traps (Fockler and Borden 1972).  The first and most numerous peak is the “mass attack” which occurs in the spring. As soon as maximum daily temperatures exceed 16° C T lineatum leave their overwintering sites in the forest floor and fly to seek suitable host material in which to produce a brood (Figure 2-4). Generally, the mass attack flight occurs in mid April. When they emerge in the spring they respond to pheromones since these insects have endured a period of reproductive diapause while overwintering (Borden 1988). It is during the spring “mass flight” that the majority of insects are trapped in pheromone traps placed out in mass trapping programs.  A second peak occurs later in the summer and is commonly referred to as the sister flight. Sister flight beetles include both current year teneral  (= brood) adults and co-dispersing parental adults  which egress the galleries along with the teneral adults. The parental adults egress the logs in synchrony with teneral adults which are flying to seek overwintering sites (McIntosh and McLean 1992). This hypothesis is supported by Lam and McLean (1992) who demonstrated the timing of peak sister flight coincides with the time of parental and teneral adult egress documented by  35  100  30  90  51  80  25 C.) 0  Il)  20  (I) (U  a)  0.  E a) E E x (U E  60 15  .  I  50  •  C.)  a) U)  10 40 5  30  (U  0  (U 0  I-  20  -5  10  -10  January  March  Febry  July  May April  June  August  Figure 2.4. Timing of the 1993 mass attack (bars) relative to temperature (line graph) in the Foreshore area of the Pacific Spirit Park, Vancouver B.C. Note the differentiation between the “mass attack” and the “sister flight” populations.  52  McIntosh and McLean (1992). This second “peak” can be detected in the traps because it is comprised of pheromone-responsive parental adults which flew in the spring “mass attack”, have completed brood production, and are egressing the logs along with teneral adults. It is probably only the parental adults which are found in the traps since the tenerals are not thought to be responsive to pheromone (Fockler and Borden 1972). Since these teneral adults will constitute the individuals of the mass attack the following year, it would be advantageous if high population areas could be predicted such that trapping intensity can be focused in those high risk areas to intercept the emerging mass attack. There is an opportunity to investigate the hypothesis that “sister flight” trap catch numbers can be used to predict numbers of beetles emerging in the “mass attack” the following spring. Specifically the objective is to develop a predictive model which can be used to estimate populations of insects emerging in the following spring.  The null hypothesis that there is no  correlation between 1993 and 1994 trap catch numbers will be tested.  2.4.3. The Study Area.  This study was conducted in the Foreshore area of the Pacific Spirit Park adjacent to the Point Grey booming area at the mouth of the Fraser River in Vancouver B.C.  This location was  selected because it lies adjacent to the Point Grey log boom storage area at the mouth of the Fraser River which provides an excellent source of beetles in an industrial setting. In addition, the study site was near to the laboratory at U.B.C. and thus traps could be easily and quickly monitored and maintained.  2.4.4. Methods and Materials.  On April 6 1993, 20 Lindgren® 12 unit multiple flrnnel traps were baited with fresh lineatin lures, and placed at 20 m spacing in a lineal array along the forest margin in the Foreshore area of  53  the Pacific Spirit Park, Vancouver B.C. These traps were used to monitor the progress of the 1993 mass attack and later in the season, some of the traps were used in the 1992 Latin square test, thus their positioning was identical to that described in section 2.2. of this chapter. In 1993, the traps were checked once a week during early April until April 20 when trap catch numbers started to rise to the first peak as shown in Figure 2-4. After this date, traps were checked every 2 days until May 13 when high trap catches signaled the beginning of the mass flight.  Traps were emptied every second day changing to daily during the peak of the mass  attack. The “sister flight” trap catches were counted from June 1 1993 because it was estimated that some of the early attacking individuals detected in the traps on April 20 could have completed brood production and left the logs by this time. The last collection of “sister flight” beetles in traps was August 20.  Because all late summer trap catch numbers were low as  compared to the mass attack numbers, all insects collected during the period of the sister flight were counted individually.  The traps used in the 1993 study were left out in exactly the same location all winter so that trap locations were constant. All traps were baited with fresh lineatin lures on March 29, 1994. The traps were first monitored on March 31 and then monitored every 4 days until April 16 when the early stages of the mass attack were detected. Traps were monitored daily from April 16 until April 19, when numbers of beetles in the traps declined rapidly. On each collection day, insects were counted manually provided there were less than 200 in the trap. However, on peak flight days when trap catches were high, beetle numbers were determined volumetrically (Shore and McLean 1985). The volumetric estimate was obtained by taking 20 samples of insects in a 10 mL Normax glass graduated cylinder and counting how many insects filled 1 mL. The calibrated estimate was 108  ±  3.09 beetles/mL.  54  2.4.5. Results. In 1993, the peak of the “sister flight” occurred on June 24 when a total of 3,228 insects were trapped. Over the 50 day sampling period a total of 13,902 sister flight beetles were collected from the 20 survey traps. In the 1994 season, 21,024 beetles were trapped between March 29-31. Temperatures became cool and precipitation slowed down the mass attack. By April 16 total trap catch increased to 43,448, reaching a peak of 71,009 trapped over the one day period between April 16-17. The total number of insects trapped during the 1994 mass attack was 208,149. To find a relationship between the 1994 trap catch data (dependent variable) were tested against the 1993 trap catch data (independent variable).  Simple linear regression was conducted to  determine the linear model of 1994 trap catches with 1993 trap catches (Figure 2-5). The equation for the linear model was determined as:  Y = 6489.288  +  5.637(Xi)  Analysis of variance was conducted to test the significance of the regression. There is a linear relationship between mass attack and sister flight trap catches (P  <  0.05; F  =  6.88; df= 1,18; r =  0.526). A residual plot revealed an apparent unequal variance of 1994 from 1993 values, thus the assumption of homogeneity of variance has been violated.  A log transformation of the 1994  values was conducted. Although the regression was still significant there was no improvement of the linear model (P <0.05), and a fl.irther residual plot of the transformed data showed increasing 1994 variability with increasing 1993.  55  20000 r0.526  18000  . .  16000 .  14000  LI..  ‘I.—  12000  Cl)  10000 0) 0)  .  .  8000 . .  6000  .  .  4000 2000 0•  0  200  I  I  400  600  800  1000  1200  1400  1600  1993 Sister Flight Figure 2-5. Correlation of 1994 mass attack catches with 1993 sister flight trap catches from 20 individual traps in the Foreshore area of the Pacific Spirit Park, Vancouver B.C.  56  2.4.6. Discussion and Conclusions.  The results of the linear regression show that there is a weak but significant correlation of 1994 mass attack trap catches with 1993 sister flight trap catches. Subsequent transformations were unsuccessfiul in reducing the increasing variance of the 1994 catches with increasing sister flight trap catches. Variability in the trap catch data suggests that this equation is probably unreliable if used as a predictor of emerging mass flight populations. This variability could have occurred as a result of sampling error, or possible errors while counting the insects. The experiment could be improved by reducing the variability of trap catch data through increasing the number of test traps to at least 30. The larger sample size would also enable an adequate residual plot to be conducted to detect heterogeneity of variance trends in the data. The scattered distribution of the data could also suggest that there may be other factors involved. Duff depth may affect dispersing mass flight beetles, while wind speed and direction, or temperature could impact both mass flight and sisterflight dispersal. If there are indeed other factors influencing the relationship between mass flight populations using sister flight populations, a more reliable equation might be developed using additional data and multiple regression techniques.  The high Y intercept coefficient value (6,489) suggests that the regression may be unstable and could result in poor predictive capabilities under variable conditions. For example, from the intercept it could be concluded that even when sister flight trap catches are zero, 6,489 insects will emerge the following spring. The success of population prediction using this method is dependent on the viability of parent beetles being captured in traps.  Through personal  observations, I have found numbers of teneral adults in some traps during this flight period. Further studies could be conducted to determine what proportion of the beetles caught in the traps during the sister flight are parental as compared with teneral adults.  57  If the correlation method were to be used operationally, it would require carefhl trap maintenance by industrial personnel or trained 1PM specialists prior to the “sister flight” period. In addition, liaison with 1PM consultants like Phero Tech Inc. for technical advice and support would be necessary. However, the development of a predictive model to produce spring flight number estimates using sister flight trap catch numbers is an area which requires further investigation.  This study needs to be expanded before a reliable predictive model describing  potential spring flight activity can become operational.. It is recommended that this study be repeated with increased sample points and replicated across a number of industrial sites. Further studies should incorporate additional variables which may better describe the relationship between the mass flight and the sister flight populations.  58 CHAPTER 3. THE  DEVELOPMENT  OF  A  DEGREE-DAY  MODEL  FOR AMBROSIA BEETLE REARED UNDER DIFFERENT TEMPERATURE REGIMES.  3.1.  Introduction.  Temporal variation in the quality and quantity of food are key components in forest insect population dynamics. To exploit their hosts, many insect species have evolved in close synchrony with host phenology (Speight and Wainhouse 1989). Some cone and seed insects, for example the spruce seed moth Cydia strobilella, must synchronize oviposition with the development of spruce flowers (Hedlin et a!. 1981), while others such as Srrobilomyia neanthracina oviposit on or near seed cones shortly after pollination (Sweeney and Turgeon 1994). 1PM strategies can be developed, through manipulating the phenomenon of insect-host synchrony, to intercept or interfere with the natural development process of the target pest. In some cases, mathematical models which describe insect development rates as a function of temperature have been used (Wagner et a!. 1984a, 1984b; Salom et aL 1987; Hagstrum and Milliken 1988;). Degree-day models have also been used to time control strategies of agricultural pests (Rice and Jones 1988; Purcell and Welter 1990; Bergh and Judd 1993) and to predict effects of accumulated temperature on development of specific forest pests (McMullen 1976). McIntosh and McLean (1992) constructed a life stage development index for use in management of T lineatum. On the basis of insect development, this index provided managers with a tool to estimate the time and location that logs were attacked by T lineatum. With an estimate of the length of time required for T lineatum to complete development, the time and location of brood beetle egress from logs could be predicted.  However this index was based on localized  information and can not be reliably used as a predictive model in other parts of the province. To be more broadly applicable, the index proposed by McIntosh and McLean (1992) needs further development, T lineatum development rates must be standardized through refinement of the existing index to include the effects of temperature variability to develop a temperature-based  59  heat sum model. This index could then be applied to predict brood egress under different climatic conditions throughout Coastal B.C.  If the time of brood beetle egress could be  accurately predicted, specific management tasks could be coordinated.  For example, timely  removal of trap bundles, or modifying boom storage protocol in areas where normally high value logs are stored. Through linicing the time of brood beetle egress with corresponding local wind speed and direction data, dispersal patterns and overwintering areas around industrial areas and dry land sorts could be predicted more accurately. Mass trapping efforts the following spring  could be focused in those areas where high overwintering populations are predicted. In this chapter, I review agroclimatology theory and current 1PM applications using degree-day methodologies to identify windows of opportunity for management and interception of target pests. Research to determine the effects of variable temperature on T lineatum development has been explored. The purpose of this research is to monitor T lineatum development reared in logs exposed to different controlled temperature conditions. The overall objective is to calculate the critical threshold temperature for beetle development.  This can then be used for calculating  degree-days and incorporated into a temperature-dependent model describing ambrosia beetle development. 3.2.  Background.  Diurnal and seasonal patterns of insect activity are determined by local weather and other environmental conditions. Knowledge of these conditions can be useful to determine a “window of opportunity” to implement management tactics.  Information describing specific times of  activity, such as emergence or flight can then be integrated into the planning phase in forest pest management strategies (Speight and Wainhouse 1989). If the biology of the target insect under various environmental conditions, for example temperature, is well understood, the opportunity to implement successful management programs is greatly enhanced (Salom et a!. 1987).  60 3.3.  Influence of Climate on Insects.  Many types of insect behaviour show definite rhythms that are correlated to rhythmic variations in environmental factors. Insects respond to a number of different external environmental stimuli. The most important environmental variables are temperature, humidity, precipitation, wind, light intensity and day length. All these factors play a major role in the development of insects and consequently they are important in timing management activities (Saunders 1976). 3.4.  Degree-Day Theory.  Temperature is a manifestation of short wave solar radiation and long wave terrestrial radiation (Griffiths 1976). Both annual and daily (diurnal) temperature patterns follow a sinusoidal curve, correlating with fluctuating patterns of solar radiation.  Annual temperatures increase, with  increasing intensity of solar radiation, from January, reaching a peak in summer months of July and August, then decline to a low during the winter months.  Diurnal temperatures follow a  similar pattern reaching a peak in the late afternoon and a low shortly before dawn (Figure 3-1). Environment Canada records daily maximum and minimum temperatures and reports the daily mean temperature as the average of the maximum and the minimum for that day (Anon 1982). Although this is not always correct over the short-term, over a period of a month, the approximation is usually good within about 0.6 °C Griffiths (1976). Since insect development rate is proportional to temperature it is possible to predict the duration of insect development even under fluctuating ambient temperatures in the field.  Units of  development are expressed as degree-hours or degree-days, which can be determined each day by calculating the difference between the developmental temperature threshold (which is species dependent), and daily mean temperature (Speight and Wainhouse 1989). The degree-day is an index which describes a measure of the difference in temperature over the period of 1 day above some baseline reference (threshold) temperature (Worrall and Elliott 1990). To determine the number of degree-days for a single day, the mean temperature is calculated by  61  18  0.10  16 14 C-) 0  a) 0. E I  Ca  a)  C.)  12  0  E Cl)  10 0.05 8 6 4 2 0.00  0 Pacific Standard Time  Figure 3-1. Diurnal mean air temperature fluctuations, as measured at 15 minute intervals and recorded by a Campbell Scientific CR10 datalogger in the University Endowment lands over a two day period between May 4-5, 1993. (Note the heat sum accumulation is in 15 minute increments above threshold temperature where TTlijeshold = 12.34 °C).  62 summing the daily maximum and the daily minimum and dividing the product by two. This mean is then subtracted from a reference threshold temperature such that each °C above that reference is counted as 1 degree-day. Due to the availability of temperature data and the ease of computation over any desired time-period, degree-day indices are routinely used in a broad number of applications (Anon 1982).  3.4.1. Accumulated heat sum. Accumulated temperatures, expressed in growing degree-hours or degree-days, are a crude indicator of the NET radiative income during the growing season (Hare and Thomas 1974). The accumulated heat sum represents a measure of the total number of days or hours above the threshold temperature, during a specified time period. The heat sum is calculated as the product of the total time exposure to a particular temperature (Te) above a given threshold (To), and is calculated using the following formula (Arnold 1959):  Heat Sum  =  Where:  Number of days or hours at Tej (Te T ) 0 -  Te = Exposed temperature ( max + mm) 2  0 = Threshold temperature T  Equation 1. 3.4.2. Growing Degree-Days. Growing degree-days are used in forestry and agriculture to aid in planning operations. In describing the impact of temperature on agricultural plant crops, Hare and Thomas (1974) stated that the underlying assumption in growing degree-days is that growth begins (or becomes significant) as air temperatures exceed a certain threshold.  63  Similarly, Worrall and Elliott (1990) describe the relationship between heat sum accumulation and bud flush initiation in the forest ecosystem. Dormant tree buds require a period of chilling before bud dormancy can be broken. Buds remain dormant through the winter months and bud flush is initiated once a heat sum is met. At this time, frost hardiness is diminishing thus the heat requirement acts to protect buds from late frosts.  Subsequent growth is then related to the  accumulation of growing degree-days above a specific threshold. The growing degree-day index can then be generated and used to plan planting and pest management operations (Anon 1982). 3.5.  Insect Development Modelling.  Entomologists have long been interested in forecasting insect life-history events. Predicting seasonal occurrence of insects is essential for scheduling sampling and control strategies (Wagner et a!. I 984a). The importance of predicting seasonal occurrence of insects has led to a great deal of research based on the formulation of mathematical models that describe insect development as a fi.inction of temperature (Wagner eta!. 1984a, 1984b; Salom eta!. 1987; Hagstrum and Milliken 1988). Since temperature has a major effect on insect development, it is important to understand development processes when applying predictive models. Degree-day models are a valuable and well-accepted tool used in the practical application of a variety of pest management strategies ranging from the effects of temperature on oviposition and brood development rates (McMullen 1976), to timing of chemical control strategies (Rice and Jones 1988; Purcell and Welter 1990). This approach is widely used because it requires minimal data for its formulation; is easy to calculate and apply; and yields approximately correct values (Wagner et a!. 1 984a). However, the empirical approach describes insect development in terms of time versus temperature, or rate versus temperature relationships. There are some aspects of empirical modelling which can provide inaccurate predictions, because measurements of insect development are unreliable at the lower and upper temperature extremes.  64  Wagner et aL (1984a) claim that the degree-day approach is only valid over intermediate temperature ranges.  They demonstrated that at the lower thermal limits, insects are able to  survive over a long time period with little or no development. Therefore, the temperature at which development first occurs i.e. the threshold temperature is difficult to measure accurately. However, as temperatures increase from the lower limits, the relationship between insect development rate over a range of different temperatures is more linear.  Using this linear  relationship, the lower temperature threshold is then determined empirically rather than experimentally.  Using regression analysis, the straight line is extrapolated through the  temperature axis (x axis intercept). Furthermore, when temperature associated with the fastest rate of development is reached, there is a rapid decline in the numbers of insects since increasing numbers of insects die when temperatures exceed the optimum. The effect of these characteristics at high temperature extremes has been well demonstrated and supported in other insect development modelling studies. McMullen (1976) found high mortality of Pissodes strobi at the highest temperature regime. Similarly, Purcell and Welter (1990) found 100% mortality in their 35 °C treatment and thus omitted the treatment from the analysis. Empirical degree-day models which use development rate versus temperature relationships are widely used to predict insect development times, because mean daily (or hourly) rates can be accumulated under fluctuating temperature environments (Wagner eta!. 1984a). The model used to predict insect development times, uses the linear portion of the curve, along which the products of development time and the number of degrees above the threshold are constant. The duration of insect development is then calculated by summing the total number of thermal units (i.e. degree-days or degree-hours) contributed at each temperature (Wagner et a!. 1 984a). The BioJlx in applied Degree-Day Models. An important feature common to all degree-day studies is the need to establish a baseline event or BIOFIX from which to base all subsequent measurements.  The accuracy of the  model is greatly enhanced through selection of a relevant biofix which corresponds to  65  predictable biological events (Welch et a?. 1981). For example, Purcell and Welter (1990) developed a degree-day model as a tool to time the application of insecticides prior to the dispersal of Calocoris norvegicus from surrounding host pistachio nut plants. In this study, the presence of the first instar nymph was used as the biofix.  From this baseline, they  predicted the period of development through to the fourth instar which was the target life stage for insecticidal applications.  In another study, Rice and Jones (1988) developed a  degree-day model to estimate the timing of post-bloom insecticide sprays targeted at the larval emergence of the peach twig borer (Anarsia lineatella), and the San Jose Scale (Quadraspidiotusperniciosus), both pests of stone fruit trees in California. The biofix used in  this study was the presence of the first male moths trapped in pheromone traps.  3.6.  Summary.  Empirical insect development models have been demonstrated to be effective in timing management intervention and pest control strategies in integrated pest management. However, no temperature based model exists to provide a basis for T lineatum management in particular the management of populations in and around contaminated sorting and storage areas. The objective of the research presented in this chapter, is to construct a temperature-dependent model to describe T lineatum development under variable temperature scenarios within controlled laboratory conditions and to validate development rates through flirther measurement and comparison of rates at ambient conditions. The rate of development of each life stage under controlled environmental conditions will be used to calculate the developmental threshold needed to develop a heat sum based degree-day model. A model which links T lineatum development to a heat sum accumulation above an environmental threshold would greatly refine the existing life stage development index developed by McIntosh and McLean (1992).  66 3.7.  A Degree-Day Model for T lineatum Development.  3.7.1. The Study Area. The study was conducted at the Forest Entomology laboratory in the Department of Forest Science at the University of British Columbia during the 1993 flight season. Field studies were established in the South Campus area of the University Endowment Lands. Insects were collected from concurrent collection and trapping studies which were conducted in the Pacific Spirit Park, in the Foreshore Park area which lies to the South of S.W. Marine Drive, adjacent to the Point Grey booming grounds at the mouth of the North Branch of the Fraser River. 3.7.2. Methods and Materials. Western hemlock host material was provided by the Greater Vancouver Regional District (GVRD). There were two main selection criteria to ensure the logs would be suitable for this study: First, the cut logs should be at least 4 months old by April 1993  -  the predicted timing of  the spring mass flight attack. Logs which had been cut in December and January were preferred, based on the need to ensure maximum susceptibility of logs as outlined in Chapter 1. Second, limitations in the size of the incubators led to an operational constraint in the selection of logs. For suitable handling and placement in the environmental chambers, it was important to select enough material with a top diameter of 30 cm. The larger butt ends of the logs were suitable for the ambient temperature treatment located at the South Campus. On March 5 1993, four western hemlock logs were selected from the GVRD dry land sort adjacent to the Second Narrows Bridge in Vancouver, B.C.  The logs were harvested from  second growth thinning operations in the Cypress Bowl area during November and December 1992.  The selected logs were cut into 3 m lengths for transportation to the South Campus  location.  67  3.7.3. Sampling Design.  In the degree-day experiment, five temperature scenarios (treatments) were established to provide a measure of insect development over a wide array of temperature treatments.  Four  environmental chambers comprising: three “Hotpack”, and one Percival® I-30B chambers were used to provide controlled laboratory environmental conditions within which to monitor insect development (Figure 3-2). The environmental chambers were pre-set and calibrated to provide constant temperature regimes of 18 °C, 20 °C, 25 °C and 30 °C.  The three Hotpacks were  calibrated at 18, 20 and 30 °C, while the Percival was run at 25 °C. The fifth treatment comprised three 3 m logs and was set up in the open in a field at the South Campus location to provide ambient temperature conditions for brood development. Insect development was monitored over time under the five different temperature regimes.  Sampling Procedure. The sampling procedure used to monitor brood development required a destructive nonreplacement sampling strategy.  Individual sample disks were marked using 1 cm masking  tape, each log bolt was subdivided into 5 cm sections so that sample discs could be cut and dissected to monitor insect development over time (Figure 3-3). A sample biscuit containing a minimum of 12 attacks was cut from one of the bolts in each chamber every 6th day. After each biscuit was removed, the cut surface of the log was covered with plastic. Each sampling day, all 12 galleries were carefully dissected and all life stages present were identified and recorded on a data sheet using the same methods as McIntosh and McLean (1992) (Appendix 3-1). In addition, conditions within the galleries such as the number of niches, and the conditions of stain were recorded. Consecutive sampling was continued for each of the four chambers and the logs at the South campus location for the duration of insect development in each treatment (Appendix 3-2).  68  Figure 3-2. Environmental chambers used for rearing T lineatum under different temperature conditions in the controlled laboratory experiments.  Figure 3-3. Environmental chamber containing log bolts with active brood production following manual inoculation with male and female T lineatum pairs. Note the boring dust at the entrance of the inoculation holes.  69 Brood mortality was measured through comparing the number of fhlly developed niches where teneral adults had been with the total number of niches including egg, larval and pupal niches. During the course of sample dissections there was an opportunity to determine the number of larval instars. At each dissection period, all undamaged larvae were collected and stored in 70% alcohol for subsequent head capsule measurement. Head capsules from 300 larvae were measured. To ensure consistency of measurement, each larval head capsule was severed from the body and laid flat on a glass microscope slide. A Nikon® binocular dissecting microscope fitted with a 2 mm eye-piece graticule with 0.01 mm increments was used to measure head capsule width. Measurements were taken under 40 x magnification at the widest point across the anterior portion of each head capsule.  Sample Preparation. On March 25 1993, the 3 m logs were further cut into 75 cm lengths, for use in the controlled environmental chambers of the laboratory study. To prevent excessive drying, both ends of each log were sealed with paraffin wax. These bolts were then stored at 7 °C in a walk-in cooler until enough insects were available for inoculation. Before placing the logs in the chambers, the surface of each bolt was scraped and punctured to enhance natural host-odor emissions. Logs to be monitored in the field at South Campus were cut into 3 m lengths and stored off the ground on three supporting logs. The cut ends of these logs were also sealed with paraffin wax to reduce drying.  3.7.4. Insect collection.  70  On Apr11 6 1993, prior to the spring flight of T lineatum, semiochemical baited Lindgren® multiple flinnel traps were set up to monitor the initiation and progress of the 1993 mass flight (Figure 3-4). A lineal array of 20 traps baited with the aggregation pheromone lineatin, was established in the forested margin along the Foreshore of the Pacific Spirit Park, parallel to and South of S.W. Marine Drive, Vancouver B.C. Traps were hung at 20 m spacing and at a height of 1.5 m above ground level such that the collecting cup hung just above the surrounding vegetation approximately 40 cm above ground level as recommended by Shore and McLean (1984). Insects collected from these traps in the early season were sexed and were used as a source of “insect inoculum” for the laboratory and field-based degree-day study.  Figure 3-4. Lindgren® 12 unit multiple funnel trap used in T lineatum flight monitoring and insect collection.  3.7.5. Inoculation Process.  71  A total of 12 inoculation holes were cut into each 5 cm sample disc. These holes were cut through the bark using a Fisher Scientific #2 (6 mm dia.) cork-borer. One freshly trapped male  and female T lineatum adult pair was inserted into each hole and the entrance to the hole sealed using discs of 1 mm gauge fibre-glass insect-screen (See Figure 3-3). When 12 insect pairs had been inoculated into every sample disc, for each of the five bolts in the first temperature regime, the bolts were stored at room temperature for one day to allow the insects time to establish. This provided the biofix from which all subsequent development times were measured.  The  inoculation procedure was repeated each day until all bolts for each of four temperature regimes were inoculated, thus, one set of logs were inoculated each day. Finally, the logs which were stored outside on the south campus were inoculated, and a five-day sampling sequence was established. Initial sampling and dissections revealed that inoculation attempts were not all successful. There was evidence that inoculated insects were escaping through the gauze sealing the entrance, and in some cases the insects were either dead or were not actively constructing galleries. Inoculation attempts in two of the controlled laboratory treatments and the ambient logs at the South Campus were clearly unsuccessful. Contingency logs were needed so that brood development and gallery productivity could be measured in each of these conditions. Upon consultation with Phero Tech field personnel, suitable logs were solicited and collected from a dry land sort operated by CRB Logging Ltd., Pemberton, B.C. On June 15, 1993, suitable western hemlock logs were selected from logs which had been attacked at the sorting area. Once selected, the location and orientation of each log was recorded. At the time of selection, the top and west facing sides of the logs were marked on each log so that each log could be placed at the south campus location in the exact orientation in which it was found.  72 On June 16, 2 logs measuring 2.5 m were placed in the South Campus location to replace the inactive log. One of the logs was for dissection to monitor brood development, while the second was used to measure the extent and success of gallery production to be linked to concurrent internal log temperature measurements. Both logs were placed adjacent and parallel to the log connected to the CR10 datalogger, which was oriented longitudinally North/South, the same orientation as when these logs were found in Pemberton. The 18 °C and the 30 °C environmental chambers were started again using additional “wild attacked” material collected from Pemberton. The start dates were June 17, 1993 for the 30 °C treatment and June 18 for the 18 °C treatment.  Initial dissection to determine baseline  development conditions revealed that only parental adults and some eggs were present in all logs collected from Pemberton.  After consulting local Pemberton temperature conditions in  conjunction with the insect development index described by McIntosh and McLean (1992) the estimated date of attack was May 12-13 (Figure 3-5).  3.7.6. Meteorological Measurements On April 21, 1993, a weather tower was erected to the North of and adjacent to the logs in the South Campus location.  Air temperature and relative humidity data were collected using a  Campbell Scientific (CS) 207 combination temperature (-36 °C to 53 °C) and relative humidity (12-100%) probe, fitted with a 12 plate gill radiation shield which was mounted on the weather tower 2.0 m above ground level. The CR10 dataloggers used in both the field and laboratory experiments were programmed to measure temperature at 5 minute intervals and to store the information at 30 minute intervals. Detailed descriptions of the wiring procedures, CR10 wiring diagram, and datalogger programs can be seen in Appendices 3-3 to 3-5.  73  35  30  25 C) 0 w20  5  0  0  5  10  15 May  20  25  30  Figure 3-5. Daily temperatures for May, 1993 as measured at the Pemberton airport. Note the first peak where mean daily temperature exceeds 16 °C (May 12-13) is the estimated time of attack of contingency logs. Source: Atmospheric Environment Service, Environment Canada.  74 Environmental Chambers. Temperature was calibrated in each of the environmental chambers before sample logs were inoculated and put into the chamber. One Copper/Constantan thermocouple was placed inside each chamber and internal temperature was measured at 1 minute intervals. Adjustments were made to the upper and lower thermostat shutoff mechanisms in each chamber, such that a constant chamber temperature could be achieved. When a constant temperature was reached, the sampling intervals were increased to 5 minutes.  The start date for each of the  environmental chambers was staggered so that a continuous sampling strategy of all treatments could be maintained. South Campus. The logs in the South Campus location were wired differently to those in the incubator study. It was important to measure the temperature distribution around the log.  Dyer (1963)  addressed the question of the distribution of attack around the circumference of the log. Parts of the log which were exposed to direct solar radiation were scarcely attacked, while logs which were shaded were attacked more uniformly around the circumference. Further studies by McLean and Borden (1977b) confirmed this and showed that the distribution of Gnathotrichus sulcatus attack was predominantly in the lower and bottom quadrants of the log and that galleries are not commonly found on the top of the log. Brood production habitat requires adequate, yet not excessive moisture and protection from temperature extremes (Kinghorn 1956). On April 14, 1993 four 3 m western hemlock logs with a bottom diameter of 45 cm positioned lengthwise North-South at the South Campus. Thermocouples were inserted beneath the bark and at 3 cm into the sapwood of the log, on four quadrants: top, east, bottom, and west (Figure 3-6). Thermocouples were inserted into each hole in the bark at an approximate angle of 15° from the bark surface such that the sensory tip lay on the surface of the sapwood. The exposed part of the wire was bent around and anchored to the log using 10 mm staples to  75  I J& Figure 3-6. Copper/Constantan thermocouples used to monitor temperature under the bark and inside the wood in four quadrants of sample logs at the South Campus location. prevent it from becoming dislodged.  An additional thermocouple (thermocouple 2) was  inserted under the bark on the top of the log. The second wire was buried under the bark and parallel to the sapwood for a distance of 7.5 cm from the sensory end. The initial program was modified to support this extra thermocouple (Appendix 3-6). The thermocouple test was run for 84 consecutive days between June 3 and August 25, 1993. These data were analyzed using a one-tailed paired t-test to compare the difference between mean temperatures measured by the two thermocouples.  The purpose of thermocouple 2 was to test the  following hypothesis: : .td = 0. There is no significant difference between mean temperatures recorded by the 0 H two thermocouples; : .td> 0. The mean temperatures recorded by the two thermocouples are significantly 1 H different (p> 0.05).  76 Between May 1 and August 27 1993, temperatures were measured both under the bark and in the wood around the circumference of the logs stored on the south campus. For a twenty-four hour period between June 1-2, 1993, mean temperatures were selected to determine diurnal patterns of temperature in all quadrants of the log.  3.7.7. Determination of Threshold Temperature (T ). 0  The environmental chambers were operating from May 1 until August 27. During T lineatum development in each of the four temperature controlled treatments, mean daily temperature was calculated using the Environment Canada method (Daily,  +  Daily/2). In my study, the  Daily and Daily values used to derive the threshold temperature represent the average daily maximum and minimum temperature recorded by the CR10 at each 15 minute interval. CR10 daily averages (sum of 15 minute CR10 averages/96) were computed over the time period 00:01 to 24:00 hours.  In addition, the total number of days required for the development of each life stage was recorded Because initial inoculations in the 18 °C treatment were unsuccessful necessitating the use of substitute “wild attacked” logs where gallery construction and egg development had already begun the median development times were used.  The proportion  (%) of each  developmental stage was calculated using cumulative counts of each life stage at each temperature (Appendix 3-7). An estimate of the time required for 50% of the individuals (T ) to reach each 50 life stage in each temperature regime was determined through interpolation between the two time intervals closest to 50% of the total number of life stages tallied. Specifically, I used the time required for T lineatum to develop from 50% of the eggs (Eggs ) to 50% of the teneral adults 50 ) with the Eggs 50 (Teneral 50 as the biofix.  77  Relevant mean  The exposure temperature (Te) is derived using the CR10 datalogger.  temperatures for each of two controlled temperature regimes can be inserted into the heat sum equation (Equation 1) shown in Section 3.4.1.  Threshold temperature was then calculated  through algebraic manipulation of the heat sum equations shown in Equation 2.  o= 20 Number Days  [  o 20 o Min 2 Max -  -  ] 0 T  =  Number Days o= 18  po 2 po Mjn 2 Max -  o 18 Maxgo Min -  -  ] 0 T  2  2 Where:  [  =  Mean temperature in 20 °C chamber  =  Mean temperature in 18 °C chamber  2  o Min 18 Max o 18 -  2 o 20 Number of days go 1 Number of days  (Teneral (Eggs ) ) 50 Number of days development at 20 °C 50 ) (Eggs 50 ) 50 = Number of days development at 18 °C (Teneral =  -  -  Equation 2.  3.7.8. Determination of Heat Sum.  In each of the five treatments, the number of degree days above threshold temperature was determined for each life stage. The number of degree-days from the biofix (i.e. presence of 50% eggs) to the point where 50% of the teneral adults were encountered was determined.  The  accumulated heat sum was calculated to determine the heat sum requirement to the point where each life stage was first encountered; reached 50% of the population (T ); and the stage where it 50 was last encountered. An establishment period was determined using the estimated May 13th timing for mass flight.  78  3.7.9. Gallery and Brood Production.  Twenty disks approximately 5 cm thick were cut from the log collected from Pemberton for use in the productivity study. Each disk was marked into quadrants identifying top, east, bottom and west aspect. Before dissection, the number of attacks found in each quadrant in all 20 replicates were counted. The disks were then carefully dissected and the number of niches in each quadrant were recorded.  Analysis of variance was conducted to test the hypothesis that there is no  difference among the number of attacks in each aspect and that attacks are uniformly distributed around the log.  A comparative analysis of successful gallery and brood production in each of the four aspects was measured by comparing the number of niches present in each quadrant. It was assumed that the number of filly elongated empty niches would represent the number of teneral adults produced from each gallery. An analysis of variance was conducted to test the hypothesis that there is no difference between the mean number of niches found in each of the four aspects. However, because the areas between the cut sample discs were irregular, it was necessary to correct the data. These data were normalized to a per attack basis and re-analyzed. 3.8.  Results.  3.8.1. Inoculations. In two of the five treatments, the insect inoculation procedure was successful. However, in the other three, insect inoculation yielded high instances of gallery abandonment and mortality. The 20 °C and 25 °C chambers were inoculated and set up first. In these two treatments inoculation was successful, however in the 18 °C, 30 °C and in the logs on south campus, gallery abandonment and mortality of inoculated insect pairs was high. In the 18 °C chamber, mortality increased from 15% at the first measurement interval to 90% 10 days later. Mortality in the 30 °C chamber increased from 50% by May 18 to 94% by June 2. In both laboratory treatments no attempt at brood production was detected (Table 3-1).  Table 3-1. Mortality in three of the five rearing regimes using laboratory inoculated GVRD logs.  79  Galleries (% of total) Regime 18°  Sampled May 29  Dissected  Initiated  20  10  Abandoned Mortality  Comments  3(15)  • Galleries 3-6mm  7 (35)  • 20%males dead in initiated galleries  300  June 3  20  1  7 (35)  12 (60)  • Brown stain  June 8  30  10  8 (27)  27 (90)  • No lateral galleries  June 13  20  4  6 (30)  10 (15)  • Insects dead, covered in mold  May 18  10  7  1(10)  5(50)  May 23  9  9  1(11)  5 (56)  • Galleries 3-6mm • Galleries 8-24mm. • No lateral galleries  May28  10  10  0(0)  2 (20)  •  June 2  20  9  1 (5)  19 (95)  •  20% male, 40% female mortality 1 elaborate gallery.  • No niches or brood. • Only 1 live beetle  June 7  10  10  0(0)  9 (90)  .  June 12  20  10  1 (5)  17 (85)  •  May29  32  4  2 (6)  26 (81)  June 3  32  10  4 (12)  18 (56)  June 8  48  4  3 (6)  41(85)  June 13  48  2  1 (2)  45 (94)  All galleries stained. Deep galleries 26-30mm. No forking or niches No niches or brood. Galleries 19-36mm  South Campus Log  All 4 live insect galleries east aspect . 90% live galleries on east and bottom quadrant . 75% live galleries on east and bottom quadrant . No brood development • Galleries 22-27 mm .  80 In the South campus log, mortality in top of the log was 100% throughout. Of the 20 active galleries 12 (60%) were in the east location; 5 (25%) were on the bottom; and 3 (15%) were on the west side; there were no active galleries found in the top part of the log. In all but one of the “active galleries” there was no attempt at brood production in spite of some long and elaborate gallery construction.  All three of these treatments were re-started using the “wild attacked”  material in the contingency logs collected from Pemberton. 3.8.2. Environmental chambers. After calibration, the mean temperature (± SD) and the total number of days required for T lineatum to complete development in each of the target temperature regimes under investigation is presented in Table 3-2.  Table 3-2. Start dates for each of the five treatments comprised of the four temperature controlled treatments and the ambient conditions. Mean environmental chamber temperature measured using the Campbell Scientific CR10 datalogger. Temperature (° C) Target  CR 10 Mean  Start  18  17.53 (±0.602)  May 14’  134  June l8’  JD  Complete  JD  Days  169  Aug. 28  240  107*  ‘  20  20.72 (±0.17)  May 17  137  July 6  187  51  25  23.25 (±1.08)  May  127  July  1  182  56  30  28.22 (±0.90)  May 13’  133  June l7’  168  July 27  208  76*  May 13’  133  June l8’  169  Aug.22  234  102*  Ambient  18.80 (±1.88)  7  Julian date Standard deviation in parentheses. Initial start date with inoculated GVRD logs. b Start date using contingency logs from Pemberton. * Number of days calculated using estimated date of attack at Pemberton (May 13 1993). 1 2 a  3.8.3.  81  Dissections.  Between May 13 and August 22 1993 at five day intervals, sample biscuits were cut in sequence from each of the five treatments.  In total, 818 galleries were dissected; of these, 542 were  dissected from logs which had been reared through different controlled temperature regimes in the environmental chambers, and 276 were dissected from the logs under ambient conditions in the South Campus (Table 3-3). A total tally of all life stages recorded in each of the temperature regimes is presented in Table 3-4. Detailed absolute and cumulative tables were constructed for each temperature regime and can be seen in Appendix 3-7. Table 3-3. Total number of galleries dissected in the environmental chambers and from the South Campus logs between May 13 and August 22, 1993. Temperature Regime  ‘  2  No. of Galleries  No. of Niches 1  No. of Empty 2  Mortality  Dissected  (Total)  Niches  (%)  18  216  802  576  28.2  20  88  199  48  75.9  25  122  243  231  4.9  30  116  331  129  14.2  Ambient  276  1107  837  24.4  Represents all niches found in the dissections; egg, larval, pupal and teneral. Represents only fi.illy developed teneral niches.  Table 3-4. Total tally of each life stage found during dissections (n = number of days). Life Stages  Temperature Regime Ambient  18  20  25  (107) 100  (51) 97  (56) 17  (76) 41  (102) 72  Li  416  118  45  34  69  L2  140  215  30  27  69  Pupae  86  125  35  21  29  393  321  50  209  83  Eggs  30  Larvae  Teneral Adults  82 Number ofLarval Instars. Results of the frequency distribution graph of head capsule measurement clearly shows that there are two distinct larval instars. Head capsule width for the first (Li) instar ranged from 0.3 75 to 0.500 mm with a mean width of 0.431 mm (± 0.023); second (L2) instar head capsule width ranged from 0.550 to 0.725 mm with a mean of 0.637 mm (± 0.034) (Figure 37).  3.8.4. Calculation of Threshold Temperature (To). The T 50 for each life stage under each temperature regime is shown in Table 3-5. To ensure the most accurate estimate two controlled temperature treatments occurring on the lineal portion of the development rate curve were used. The 18 °C and 20 °C treatments were selected and used to derive the threshold temperature. The threshold temperature (T ) was determined through solving for T 0 0 in Equation 3 below. At 18° C the number of days o for development from 50% eggs to 50% tenerals required 76.85 18  -  38.03 days for a total of 38.82 days. At 20 °C the number of days o for development from 50% 20 eggs to 50% teneral adults was 35.50  -  13.27 days for a total of 22.23 days. These development  times together with the Te at 18 °C and 20 °C were inserted into the equations and solved for T . 0  Number Days o 20  [  o Min 0 Max o 20 -  -  ] 0 T  =  Number Days o =  [  Max igo Min o T 18 0 -  2 Where:  o 20 o Mifl 20 Max -  -  J  2 =  20.93 °C  o 20 Number of days  =  22.23  =  17.26 °C  Number of days o 18  =  38.82  2 o Min 18 Max o 18 -  2 Equation 3. Thus, the calculated threshold temperature 0 (T was 12.34 °C. )  83  60  -  Second Instar Larvae (L2)  50  40  0.637mm (± 0.034)  First Instar Larvae (LI) 0.431mm (± 0.023) -  -  0  a)  30  -  U-  20  10  0  035  0.40  I  I  I  0.45  0.50  0.55  0.60  I  I  0.65  0.70  Head Capsule width (mm)  0.75  Figure 3-7. T lineatum head capsule frequency distribution clearly showing the presence of two larval instars (n = 300). Note mean head capsule width (mm) and standard deviation for each larval instar are labeled above each distribution.  Table 3-5  Time (T ) required for 50% of each life stage to develop under five different 50 temperature scenarios.  Stage  84  Number of Days for 50% Development by Temperature Regime Ambient 25 30 18 20  Eggs  33.16  38.03  13.27  14.85  35.68  Li  35.96  46.70  19.16  19.29  40.75  L2  45.54  54.58  23.85  22.98  54.34  Pupae  54.58  71.04  24.09  27.50  56.35  Teneral adults  64.94  76.85  35.50  39.31  62.50  Larvae  3.8.5. Calculation of Heat Sum Accumulation. The total number of days above threshold temperature was calculated (Table 3-6). For the purposes of comparison, the results of this analysis can be seen in Figure 3-8 in a format similar to that used by McIntosh and McLean (1992). The heat sum accumulation was calculated using the 12.34° C threshold temperature described in section 3.8.4. Table 3-6. Total number of days for brood development from the gallery development biofix to the last life stage present under the five temperature regimes from May 13 and August 22, 1993. Standard deviation indicated in parentheses. Temp.  Mean Temp. (°C)  Mean Temp. (°C)  No. of Days for  Heat Sum  Regime  (max+min)12  (CR10)  Development  (> 12.34 °C)  18  17.26 (±1.62)  17.53 (±0.60)  107  540.44  20  20.93 (±0.17)  20.72 (±0.17)  51  421.10  25  23.69 (± 1.53) 28.80 (±1.01)  23.25 (± 1.08) 28.22 (±0.90)  56  612.33  76  1038.87  17.34 (±2.11)  18.80 (±1.88)  102  520.38  30 Ambient 1  Since attack occurred in Pemberton, local temperatures were used to calculate the heat sum accumulation prior to introduction to the environmental chambers or the South Campus locations.  85 3.8.6. Thermocouple Test. It can be concluded from the results of the paired-sample t-test that there is a significant difference in mean temperature measurements at 95% confidence (Table 3-7).  Table 3-7  Results of the one-tailed paired-sample t-test to test the significance of thermocouple placement on mean temperature measurements  Thermocouple  Number of  Mean  Observations  Temperature  Thermocouple #1  84  21.562  3.042  Thermocouple #2  84  20.664  3.0 17  Position  *  1  Significantly different (P > 0.05; t 83 Standard deviation.  ±  SD’  t  calc  7.869*  1.664).  Log Temperatures. Between May 1 and August 27, 1993, temperatures were measured around the circumference of the logs stored on the south campus under the bark and in the wood at a depth where brood development would occur.  The highest temperature (47.51 °C) was recorded on  August 5 in the bark on the top of the log. Lowest temperatures (5.59 °C) were recorded on May 2 under the bark on the top of the log. Sunmiary data of daily maxima, minima and averages are shown in Appendix 3-8.  86  =  50% of Population  =  Duration (No days)  July 18, First niches visible after 324 Degree Days 67 days after initial attack  .1 1  [ Period of Gallery  I  LI Larvae  Eggs  (  establishment 0  100  200  I  I  I  300  400  500  600  Number of degree-days from log attack  Figure 3-8.  Chart showing the number of degree-days above 12.34 °C for each T lineatum life  stage. Note, since eggs were already present in the Pemberton logs, an estimate of 21 days before the first presence of eggs was estimated from the May 13 initial flight after McIntosh and McLean (1992).  87  Diurnal patterns in the bark and in the wood followed a similar sigmoidal pattern, with the highest temperatures occurring on the top and west-facing surfaces (Figure 3-9). Peak mean daily temperatures occurred for both wood and bark typically at around 17:00 hours on the top of the log, with a two hour delay before peak temperatures were found in the west facing surfaces at 19:00 hours PST. Mean daily temperatures in both bark and wood measurements reached a minimum at about 5:00 hours PST, just before dawn (Figure 3-9a). Mean diurnal bark and wood temperatures on the bottom and east portions of the log fluctuated more closely around the mean air temperatures. Bark and wood temperatures in these quadrants remained more constant. Air temperatures dropped below log temperatures between 20:00 hours and 5:00 hours the next day.  During the heat of the day, air  temperatures remained above those in the wood and bark on the bottom of the log and below those on the east surface.  3.8.7. Gallery and Brood Production. The results of the ANOVA revealed that there is a significant difference (c  =  0.05) between the  number of attacks in the four quadrants and that the null hypothesis must be rejected. Since a significant difference in the distribution of attacks around the log was detected, a Scheffés pairwise multiple comparison test was conducted to test for differences between aspect strata. The highest number of attacks was in the west (6.0 ± 2.92), followed closely by the bottom, with the east and top showing the least number of attacks. The mean number of attacks found in the bottom and west aspects were significantly different from the number in the top and the east. There was no difference detected between the mean number of attacks found in the west and those found in the bottom of the log.  88 40  35  —  I  -e—  -  —A——  I  I  Teniperaturejunel,1993  -  ——  30  I  I  I  I  WOOD  -  Mr temperature Top West  25 a20  E  15 10-  50  I  -  0  300  I  I  I  I  I  I  600  900  1200  I  1500  1800  2100  2400  Pacific Standard Time 40  B) C-) 0  I  -  I  I  I  I  I  I  I  35 30  25 L.  a2o E a)  1%?  10 50  I  -  o  300  600  900  I  I  I  1200  I  I  1500  I  I  I  1800  I  I  2100  2400  Pacific Standard Time Figure 3-9.  Diurnal log and air temperatures measured at the South Campus over a two-day period between June 1-2, 1993. Air temperature measurements and measurements in all four quadrants in A) the wood; and B) the bark of the log, were taken at 30 minute intervals.  89 The analysis of variance to test differences between the mean number of niches found in each of the four aspects revealed that at least one of the means was significantly different from the rest. Mean number of niches were fi.irther analyzed using the multiple comparison test to determine significant differences between strata means.  The highest number of niches were found in the bottom section of the log (34.15  ± 16.65),  while  the least occurred in the top (4.60 ± 6.26). Dissections showed that at least three times as many niches were found in the bottom quadrant than on any other aspect (Table 3-8). Because the surface areas between the cut sample disks were irregular, so it was necessary to correct the data by normalizing to a per attack basis and re-tested. The results of the ANOVA reveal that at least one of the aspects is significantly different. The highest number of niches per attack occurred in the bottom section of the log, while the lowest occurred in the west section of the log, closely followed by the top (Table 3-8).  Table 3-8. Comparison of the mean number of attacks, niches, and niches per attack by quadrant using the Scheffé pairwise multiple comparison test (n = 20).  1 2 4  Aspect  Number of Attacks 1 4 Mean ) 5 (±SD  Top  b 215  (1.57)  b 460  (6.26)  East  b 210  (0.97)  b 1025  (8.78)  ab 511  (3.71)  Bottom  4.70a  (2.23)  34.15 a  (16.65)  8.22a  (4.72)  West  6.OOa  (2.92)  11.40’  (8.53)  Number of Niches 2 4 Mean ) 5 (±SD  3 No. of Niches/Attack ) 5 (±SD 4 Mean (4.57)  (1.35)  F=7.34; P<0.001. F=6.89; P<0.001. F=8.61; P<0.001. Means within each column followed by the same letter are not significantly different using Scheffé allowances at P = 0.05. Standard deviation indicated in parentheses.  3.9.  90  Discussion.  The use of degree-day models to predict specific life occurrences to focus the timing of management intervention strategies is an acceptable and well-documented method in applied pest management (McMullen 1976, Salom eta!. 1987, Rice and Jones 1988, Purcell and Welter 1990). Although linear heat-sum models are valuable tools, the predictive capabilities of the linear heatunit models can be erroneous due to variable development rates of different insect stages (Arnold 1959).  Developmental profiles of poikilothermic organisms have been described using  mathematical functions which are designed to account for the temperature effect on the development times of different insect life stages (Hagstrum and Milliken 1988). The stochastic models proposed by  Salom et a!. (1987) and Hagstrum and Milliken (1988) used constant  temperature experiments to describe each life stage as a function of probability distributions of individuals in a population. Over a wide range of temperatures, the lower temperature threshold is quite different depending on the target insect and its relationship with its host. In this study, the calculated threshold temperature (T ) of 12.34 °C was relatively high in 0 comparison to the 6.39° C lower temperature threshold calculated for the mirid bug Calocoris norvegicus (Purcell and Welter 1990), or the 7.2 °C threshold published for the White pine weevil Pissodes strobi (Peck) (McMullen 1976). The mind bug is an agricultural pest of pistachio nut trees. The nymphs develop in annual weeds and disperse to the host trees at a time when the nuts are mature and susceptible to damage (Purcell and Welter 1990). White pine weevils overwinter as adults in the duff beneath host trees and disperse in the spring to feed on the phloem of Sitka spruce and Engelmann spruce (Picea engelmanii Hopkins.), before mating and oviposition occurs (Furniss and Carolin 1977). Both of these insects rely on plants as a source of nourishment and their dispersal is closely synchronized with the host. It is possible that for these two species there is an ecological advantage in a lower temperature threshold that ensures that patterns of feeding are synchronous with maximum susceptibility of the host plant.  91 In contrast, T lineatum is a xylomycetophatous insect (Borden 1988) which must locate susceptible host logs, mate and initiate gallery construction and inoculate the spores of its associated fungus in the host log before it can feed and replenish severely depleted energy reserves. Nijholt (1967) reported that at the time of the spring mass attack, T lineatum have metabolized 50% of their body fat. As outlined in Section 1.2.2. in Chapter 1, this suggests that T lineatum needs to locate host logs rapidly to find suitable mates and replenish energy reserves. Additionally T lineatum is in competition with other scolytidae such as Gnathotrichus spp and thus must fly to locate host logs and ensure it occupies its niche before this major competitor (Lindgren and Borden 1983).  It is therefore possible that there may be some ecological advantage in a high threshold temperature for T lineatum development.  In the spring as temperatures increase, the rate of  fermentation in susceptible logs will increase. This will increase the abundance of host volatiles and most likely will improve the host-finding capabilities of the emerging T lineatum beetles. There are other species with higher threshold temperatures, e.g. the lepidopteran peach twig borer Anarsia lineatella Zeller requires a 16 °C threshold (Rice and Jones 1988).  3.9.1. Inoculation. The results of the manual inoculations attempted in this study clearly demonstrate the importance of the very specialized relationship between T lineatum and its host discussed by Borden (1988).  The limited success of forced inoculation in these experiments could have  resulted from either host or insect compatibility. Host Suitability. Variable suitability of host material could have caused the high proportion of abandonment encountered in the 18 °C, 30 °C and logs out at the South Campus. These logs had few active galleries and a high proportion of individuals abandoned the logs or escaped from the  92 inoculation hole. In addition, unsuitable host material coupled with stressftul temperature conditions could also have caused the high mortality and host rejection presented in Table 3-1. It is possible that there may have been a difference in the suitability of the second growth material used in the inoculated logs as compared to the naturally attacked old growth supplementary logs collected from Pemberton. In an experiment of this nature it is critical that the developing broods are reared through in suitable host material and that there is no resultant stress from their host environment. In the natural environment, beetles will not remain in an unsuitable host and post mass flight attack trap catches indicate the presence of displaced beetles searching for suitable host materials (Borden 1988). The experimental design was such that the differing temperature regimes should have been the only limiting factor influencing the rates of brood development, however when the suitability of the host material is variable, an uncontrolled qualitative variable is added into the experiment for which it is very difficult to assign any measure of predictability. It is clear from the results of this experiment that the host material I obtained from the GVRD was too fresh and was not suitable for brood production. This experiment could have been improved by using naturally attacked material instead of inoculating insects into host material of unknown suitability. One solution might be to cut logs specifically for inoculation to ensure that the age of the log since falling is known, however, there is still no guarantee that the log will be suitable for brood production and the beetles could still abandon inoculated galleries. If this experiment were to be repeated, I would recommend the use of naturally attacked material. Insect Compatibility. In addition to the condition of the host material, many questions arise as to the condition of the insects used in this study. Very little is understood about the bond between T lineatum pairs and the literature concerning the compatibility requirements of mating couples is lacking. Apparently, the males do not need flight exercise before they mate, and there is evidence that  93 mating activity can occur in the forest floor prior to spring emergence (Fockler and Borden 1972). Chapman (1954) observed that mating occurs outside the galleries and that the testes become inactive once the male is inside the host.  In view of the amount of gallery  abandonment, it may be critical that the insects be allowed to select their own mate. However, there is little in the literature addressing the matter of how often males can mate and with how many partners.  There are many questions which arise from this component of the study.  Apart from the suitability of the host material there are some a number of explanations why inoculated beetles abandoned the logs. First there is the question of insect compatibility. If mating has already occurred before beetles are placed with a second partner, it is unknown if this second couple will mate. For example, it is possible that males which have already mated (passed spermatophores) before being placed in the inoculation hole do not mate again. Ecologically, it could be argued that there is a genetic advantage to support multiple mating by male T lineatum, however the pairbonding behaviour displayed between male and female in gallery construction suggests monogamy. The opposite scenario could also be considered. A female beetle which has already mated and has been fertilized prior to inoculation in the log with an unmated male may not mate a second time. If this actually happens, it is unknown if the unmated male will remain as a partner and continue in the gallery construction. There are strong ecological grounds to suspect that in this scenario, the male will abandon the gallery. If the unmated male is unable to pass his genetic material it is most likely that he will leave the gallery in search a receptive mate. It is probably these individuals which abandon the gallery after inoculation. A number of opportunities exist when random mating could occur before beetles were placed into the inoculation holes in the logs used in this study. Fockler and Borden (1972) have already established that mating can occur in the duff shortly after overwintering diapause is broken. In addition, there is a high probability that mating occurred in, on and around the  94 multiple funnel traps simply due to the aggregation of many beetles of both sexes. Mating could also have occurred in the collecting cups of the traps as well as in the storage jars at the laboratory. A third possible impediment to successful inoculation could have been due to excessive handling of the insects. The insects used in this experiment were first trapped and collected from pheromone traps, sexed and stored in holding containers in the refrigerator (4 °C) and then manually placed in the inoculation holes. If inoculation methods are to be used, it is believed that better results may be achieved through minimized insect handling.  3.9.2. Environmental Chambers. Insect development rates were variable in each of the five temperature regimes. Development rate increased from the ambient and 18 °C treatments and reached a peak in the region of the 20 °C and 25 °C treatments. However in the 20 °C treatment many of the galleries dissected towards the end of the developmental period contained dead insects and partially developed galleries. This suggests that the host material in this treatment may have been marginal in terms of suitability as discussed in Section 3.8.1.  Insect development in this treatment may have been influenced  through the compounded effect of stressful temperature and marginally suitable host material. The high mortality in 20 °C treatment and relatively low brood productivity in the 25 °C treatment suggests that these two regimes are at the upper limit of development and probably exceed the linear portion of the development rate curve. In the 30 °C treatment, development time increased probably as a result of stress and high mortality.  This result is expected and is the reason for the stochastic approach proposed by  Wagner eta!. 1984b. The results in this part of the study support hypotheses presented by Salom et a!. (1987) and Purcell and Welter (1990). Salom et aL (1987) found that there is a narrow range of temperatures in which Hylobius pales could develop. Larvae did not survive longer than  95  three days at the lower temperature threshold, and they experienced high mortality in higher temperature treatments. The heat sum accumulation above 12.34 °C required to complete development in the 18 °C treatment (540.44) and that in the ambient South Campus log (520.38) were quite similar. Naturally attacked material from Pemberton was used for insect rearing in both these treatments, thus the effects of unsuitable host material can be eliminated. In addition the brood productivity in the galleries in the 30 °C treatment exceeded that in the 20 °C and 25 °C treatments. This is probably due to the use of wild attacked logs for this treatment so galleries were well established in the field as opposed to the manually inoculated logs used in the 20 °C and 25 °C treatments.  3.9.3. Experimental Design. The quality of the degree-day predictor should be improved through replication of sampling within each temperature regime. The best way to improve the precision is to increase the number of observations within each of the temperatures under investigation. Wagner et al. (1 984a) claim the degree-day approach is only valid over intermediate temperature ranges. The high degree of variability in insect development at the lower temperature extremes was discussed by Wagner et al. (1984b), and within the high temperature range insect mortality impacts the accuracy of temperature threshold estimation. If this experiment were to be repeated it is recommended that lower temperature regimes should be selected. This would ensure that sampling was conducted on the linear portion of the T lineatum development curve.  Temperature regimes should be  selected which span the 12.34 °C threshold derived in this study. Regimes might include a low temperature of 13 °C, 14°C, 15°C, 18°C and 20 °C as the upper limit might enable empirical estimation of the temperature threshold through extrapolation of the regression line through the x  axis and provide a more accurate mathematical estimate. In addition replication particularly in the lower end of the thermal scale to provide a better regression equation.  96  3.9.4. Temperatures Inside Log. The distribution of attack around the log has been studied in detail by Prebble and Graham (1957), and McLean and Borden (1977). In exposed logs, Prebble and Graham (1957) found that the most exposed quarter was the least attacked. In shaded logs, they found that the attack intensity was approximately even on all quarters. When they combined the data from all their logs they determined that 52% of the T lineatum attacks occurred in the lower half of the log while in Gnathotrichus spp. 62% occurred on the bottom half of the log. Studies conducted by McLean and Borden (1977) were in agreement with the earlier study by Prebble and Graham (1957). In their study McLean and Borden (1977) showed that attacks were lowest on the top surface of the log while attack intensity was approximately equally distributed on both sides and the bottom of the logs. Neither of these studies linked attack distribution to temperature conditions in each part of the log. The results of the South Campus study described in Section 3.7.6. are in agreement with the findings of both of the previously mentioned studies. In spite of the fact that there were more attacks in the West quadrant than in the rest of the log, survivorship as determined by the number of niches per attack was the lowest.  Clearly the most productive part of the log for brood  development is in the bottom and east quadrants of the log.  The data shown in Figure 3-9  demonstrate how temperatures in the log on the bottom and eastern part of the log closely follow the diurnal fluctuations characteristic to ambient air temperature. Internal log conditions in these two quadrants are not subject to extreme fluctuations in diurnal temperature.  Temperatures in the top and the west quadrants of the log can reach 35 °C in the afternoon which appears to exceed the upper threshold for successful brood development. Brood reared at 30 °C under controlled temperatures were severely retarded in their development and were beyond the upper development threshold limits. In view of the extreme conditions in the top and west sections of the log, beetle survivorship in these regions is restricted. Attempts at gallery  97 construction and brood development in this section of the log will very likely be unsuccessful, and beetles attempting to establish brood under these conditions will probably abandon in search of a new location. Thus the wisdom of chemical control activities conducted in the 1960’s where flat run log-booms were sprayed with chemical insecticides (Richmond 1961) is questionable.  In a study of this nature where accurate temperature measurements are necessary, careless placement of thermocouples can be a source of systematic bias. The results of the thermocouple test suggest that thermocouple placement can significantly influence temperature measurements. In this study, initial thermocouples placed in the bark consistently recorded higher temperatures than the second attachment method where the wires were buried at a greater distance from the sensory tip. In this study the bark measurements were not so critical to the outcome as the internal wood temperatures. However, thermocouples recording internal temperature conditions in the wood were buried deep (see Section 3.7.6.) and there was at least 7.5 cm of wire buried between the sensory tip and the outside of the log. The effects of heat conduction resulting from thermocouple placement should be considered in any further experiments where the discrepancy in temperature caused by thermocouple placement exceeds the allowable error as defined during the experimental design.  98 3.10  Conclusions and Recommendations  Trypodendron lineatum is a serious pest of valuable logs harvested in coastal B.C. Each year,  millions of dollars are lost through degrade caused by these beetles and in spite of almost 50 years of research, inventory is still attacked in the forest and infested inventory brought into storage areas. Recommendations to control this beetle commonly emphasize improved management and tight inventory control as the foundation for all proposed 1PM strategies. In view of the current philosophy regarding the multiple use of forest resources and environmental constraints regarding harvest levels it is critical that the value of wood fibre is conserved from the stump to the mill. All management efforts to improve management activities and inventory flow to minimize the degrade sustained in the forest will be lost if clear wood is allowed to be attacked while in storage prior to milling. If the forest industry is truly committed to addressing the issue of ambrosia beetle management, it is important that a concerted beetle management effort is implemented at the local level. Management would be greatly improved if qualified technical personnel, in liaison with professional pest management consultants, could operate on behalf of the forest company to provide local knowledge and experience of each of the industrial sites to be accountable for ambrosia beetle issues and to monitor and take responsibility for site specific ambrosia beetle management. The degree-day approach has been demonstrated to be a highly effective and versatile tool for operational use in management decision making (McMullen 1976; Rice and Jones 1988; Purcell and Welter 1990). The results of my research suggest that a temperature dependent heat-sum based model of T lineatum development could be used as a predictive tool for use in the application of 1PM strategies to protect log inventory in industrial sorting and storage areas. The heat sum calculated life cycle will allow dry land sort managers to establish where logs were when they were attacked, and enable them to predict when beetles will be present in logs passing  99 through the dry-land sort and when these beetles will egress the booms in the storage areas. The use of the calculated heat sum will result in the following advantages:  3.10.1. Widespread application of the Life Stage Development Index. In the management of beetle populations around restricted industrial sorting and storage areas, it is critical that the development and dispersal of the developing brood beetles is known.  A  generalized index which describes brood development as a function of different temperature conditions, can be universally used in B.C. and thus will be a significant improvement of the existing index reported by McIntosh and McLean (1992). Using the threshold temperature of 12.34 °C derived in this study, beetle development can be described at the local level by calculating the accumulated heat sum above the threshold. The prediction of brood beetle egress is of paramount importance and thus the first signs of brood activity inside the log must be determined. Brood activity inside the log is indicated by the presence of empty niches signifjing the point in time where beetles leave their niches and begin maturation feeding. This activity can be used as an indicator as to when the parental adults will leave the logs and thus will provide the cue for initiating late season trapping surveys. In this study the first signs of empty niches in the 18 °C treatment occurred at the point where the accumulated heat sum reached 324.  In 1993, a heat sum accumulation of 324 degree-days  corresponds with a calendar date of July 18 (see Figure 3-9). With this information, the dry-land sort manager can expect brood egress to occur. Boom storage configuration could be modified at this time, such that logs are not stored in areas where high value logs are commonly stored and thus minimize the risk of contamination in those areas. Similarly, through observation of weather patterns around the dry-land sort, in particular wind speed and direction, high hazard areas can be predicted and spot and mass trapping efforts which would be initiated the following spring could be focused in these areas.  100 3.10.2. Management of Trap Bundles in Dry-land Sorting Areas. Knowledge related to the timing of brood egress from logs will provide the basis for more informed decisions regarding the management of trap bundles deployed to protect log inventory in sorting and storage areas. It is common practice in dry land sorting areas, to strategically place trap bundles around the site to intercept the mass attacking beetles as they fly from the adjacent forest margin in the spring. With this population reduction tactic, the objective is to attract and “absorb” mass attacking beetles in cull logs, before they select high value inventory stored on the site. However, the key to success of this tactic is the timely removal and disposal of attacked trap logs. If trap bundles are left on site past the date of brood beetle egress, these logs will contribute to the contamination of the dry land sort. Instead of serving to reduce local beetle populations these logs would serve as a breeding ground for ambrosia beetles.  Consequently, inaction  resulting in the failure to remove trap logs will contribute to increasing populations in this area. The cumulative heat sum for T lineatum could be monitored at any dry land sort or industrial site, using local temperature and wind data either from dataloggers collecting climatological data “on site”, or using Environment Canada climate data as measured at the nearest airfield. With this information, the accumulation of degree-days could be monitored and the period of log egress could be predicted.  Trap log bundles could then be removed in a timely fashion after the  predicted number of degree-days have accumulated when the first tenerals are found in the log.  There is an opportunity to develop a pest management strategy targeted at controlling resident beetle populations at each of the industrial areas using current mass trapping and population reduction techniques as an 1PM strategy. The ability to predict log egress could be used to time maintenance of pheromone traps used to monitor sister flight beetles around the site to estimate resident population levels in and around the dry land sort.  101 3.10.3. Further Research and Development opportunities.  Diurnal patterns of brood egress have not been successfully investigated. It is still unknown if beetle egress is constant throughout the day, or if a peak egress period exists. The significance of this information is in the opportunity to further focus predictive capabilities to identi1’ overwintering sites. Using the degree-day model described in this study, dispersal patterns must be predicted using a diurnal average wind speed and direction value, which may provide misleading information as to potential beetle overwintering locations. If a specific time of day exists when peak egress occurs, wind speed and direction at that particular time would result in a greatly improved predictive capacity.  102  3.11. 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Sitka spruce weevil (Pissodes strobi) population dynamics and control: A simulation model based on field relationships. Can. For. Serv. Pa. For. Cen. Information Report BC-X-288 (1987) 20 pp.  109 Miller, A.V. and S.M. Craig (Eds.) 1980. Handbook for Pesticide Applicators and Pesticide Dispensers. Pesticide Control Branch., MOE, Victoria. 233 pp. Moeck, H.A. 1970. Ethanol as a primary attractant for the ambrosia beetle Trypodendron lineatum (Coleoptera: Scolytidae). Can. Entomol. 102: 985-995. Moeck, H.A. 1971. Field test of ethanol as a scolytid attractant. Can. Dept. Fish. and For. Bi Mon. Res. Notes. 27(2): 11-12. Nigham, P.C. 1969. Laboratory evaluation of twelve insecticides against adult ambrosia beetles. Can. Dep. Fish. and For. Bi-Mon. Res Notes 25(2): 11-12. Nijholt, W.W. 1967. Moisture and fat content in the ambrosia beetle Trypodendron lineatum (Oliv.) J. Entomol Soc Brit. Columbia. 64: 5 1-55. Nijholt, W.W. 1969. Fat content of the ambrosia beetle Trypodendron lineatum (Oliv.) during attack and brood production. J. Entomol Soc Brit. Columbia. 66: 29-31. Nijholt, W.W. 1973. Ambrosia beetle: Ambrosia beetle attacks delayed by turpentine oil. Can. Dep. Fish. and For., Bi-mon. Res. Notes 29(6): 36. Nijholt, W.W. 1978. Ambrosia beetle: A menace to the forest industry. Can. For. Res. Cen. Rep. BC-P-25. 8 pp. Nijholt, W.W. 1979. The striped ambrosia beetle Trypodendron lineatum (Olivier). An annotated bibliography. Can. For. Serv. Rep. C-X-121. Nijholt, W.W and J. SchOnherr. 1976. Chemical response behaviour of scolytids in West Germany and western Canada. Bi-mon. Res. Notes 32: 31-32. Novak, V. 1960. Natural enemies and diseases of the striped ambrosia beetle Tiypodendron lineatum Oliv. Zool Listy 9(4): 309-322. Novak, V. 1962. Investigation of diapause in the ambrosia beetles Tiypodendron lineatum 01. Commun. Inst. For. Cech. 3: 23-43. Orbay, L., J.A. McLean, B.J. Sauder and P. L. Cottell. 1994. Economic losses resulting from ambrosia beetle infestation of sawlogs in coastal British Columbia, Canada. Can J. For. Res. 24: In press. Overend, M. 1978. How loggers stem menace of the ambrosia beetle. Can. For., Industries. 98(8): 53-54. Panshin, A.J. and C. De Zeeuw. 1977. Textbook of Wood Technology: Structure, identification, properties, and uses of the commercial woods of the United States and Canada. (4 Ed.) McGraw-Hill Book Company, New York. 722 pp.  110 Prazak, R. 1991. Studies on indirect infection of Trypodendron lineatum Oliv. with Beauveria bassiana. (Bals.) Vuill. J. Appi. Entomol. 115(5): 431-441. Prebble, M. L. and K. Graham. 1957. Studies of attack by ambrosia beetles in softwood logs on Vancouver Island, British Columbia. For. Sci. 3: 90-112. Purcell, M. and S. Welter. 1990. Degree-day model for development of Calocoris norvegicus (Hemiptera: Miridae) and timing of management strategies. Environ. Entomol. 19(4): 848-853. Reisch, J. 1967. Barked softwood suffers less damage from Trypodendron lineatum. Holzforsch. Zentralbl. 93(143): 2221 Rice, R.E. and R.A. Jones. 1988. Timing post-bloom sprays for peach twig borer (Lepidoptera: Gelichiidae) and San Jose Scale (Homoptera: Diaspididae). J. Econ. Entomol. 81(1): 293299. Richmond, H.A. 1961. Helicopters protect log booms in B.C. Can. Lumberman. Dec 1961. Richmond, HA. 1962. Ambrosia beetle control. Experimental spraying of bundled logs on flat cars, Crown Zellerbach operations, Nanaimo Lakes. B.C. Loggers’ Assoc. Rept. 1962. Richmond, H.A. 1966. Tests of four new insecticides for the protection of sawlogs from ambrosia beetle attack. Entomol. Soc. Brit. Columbia. March: 5 pp. Richmond, H.A. 1969. Apetite for wood. Chemicals help but good woods management remains best way to control destructive ambrosia beetle. B.C. Lumberman 53(8): 34-36. Richmond, H.A. and W.W. Nijholt 1972. Water misting for log protection from ambrosia beetles in B.C.. Can. For. Serv., Pac. For. Res. Cent. Inf Rep. BC-P-4-72. Richmond, H.A. 1986. Forest Entomology: From Packhorse to Helicopter. Management Report No 8, ISSN 07 10-7935 44 pp.  B.C. Pest  Richter, H. 1918. Uber die lebensweise und bekampfung des Nutzholzborkenkafers Xyloterus lineatus 01. Forstwiss. Zentralbl. 40: 24 1-244. Rudinsky, J.A. and G.E. Daterman. 1964. Field studies on flight patterns and olfactory responses of ambrosia beetles in Douglas-fir forests of Western Oregon. Can. Entomol. 96(10): 1339-1352. Rummukainen, U. 1964. On the deterioration of green softwood caused by insects and its chemical control. Commun. Inst. For. Fenn. 28(5): 1-67.  111 Salom, S.M., F.M. Stephen and L.C. Thompson. 1987. Development rates and a temperaturedependent model of Pales weevil, Hylobius pales (Herbst), development. Environ. Entomol. 16: 956-962. Salom, S. M. and J.A. McLean. 1988. Semiochemicals for capturing the ambrosia beetle Trypodendron lineatum in multiple-fhnnel traps in British Columbia. J. Entomol. Soc. Brit. Columbia. 85: 34-39. Salom, S. M. and J.A. McLean. 1989. Influence of wind on the spring flight of Trypodendron lineatum (Olivier) (Coleoptera: Scolytidae) in a second-growth coniferous forest. Can. Entomol. 121: 109-1 19. Salom, S. M. and J.A. McLean. 1990a. Flight and landing behavior of Tiypodendron lineatum (Coleoptera: Scolytidae) in response to different semiochemicals. 3. Chem. Ecol. 16(8): 2589-2603. Salom, S. M. and J.A. McLean. 1990b. Flight behavior of scolytid beetle in response to semiochemicals at different wind speeds. J. Chem. Ecol. 17(3): 647-661. Salom, S.M. and J.A. McLean. 1991. Environmental influences on dispersal of Trjpodendron lineatum (Coleoptera: Scolytidae). Environ. Entomol. 20(2): 565-576. Saunders, D.S. 1976. Insect Clocks. Volume 54., International Series in Pure and Applied Biology. Division: Zoology. Pergamon Press, Ontario, Canada. 280 pp. Schindler, U. 1967. Borkenkaferbekampfung unter besonderer berucksichtigung der rindenbruter an fichte und kiefer sowie des gestreiften nutzholzborkenkäfers. Forsttech Inform. 3: 1523. Schindler, U. 1968a. Die forstschutzlage in Nordwestdeutschland. Alleg. Forststz. 23: 187-192. Schindler, U. 1968b. Nutzholzborkenkafer-bekampfung mit chemischen mitteln in abhangigkeit von den biologischen grundlagen. Forst. Holzwirt. 23(13): 1-3. Schindler, U. 1970. Further experience in the control of Trypodendron lineatum. Zentralbl. 96: 505-506.  Holz.  Schneider, I. and J.A. Rudinsky. 1969. Anatomical and biological changes in internal organs of adult Trypodendron lineatum, Gnathoirichus retusus and G. sulcatus (Coleoptera: Scolytidae). Ann. Entomol. Soc. Am. 62: 995-1003. Schonherr, 3. 1958. Die dampfung, em weg zur entseuchung des von nutzholzborkenkafer Xylolerus lineatus befallennen holzes. Forst Jagd. 8(5): 227-228. Schwerdtfeger, F. 1964. Wie kann der gestreifte Nutzholzborkenkäfer bekampft werden?. Holzzentralbl. 90: 33 1-332.  112  Shore, T.L. 1985. Ambrosia beetles. Pest leaflet #72. Pac. For. Res. Cen. FPL 72. 4 pp. Shore, T.L. and J.A. McLean. 1984. The effect of height of pheromone-baited traps on catches of the ambrosia beetle Trypodendron lineatum. J. Entomol. Soc. Brit. Columbia 81: 1-2. Shore, T.L. and J.A. McLean. 1985. A survey for the ambrosia beetles Trypodendron lineatum and Gnathotrichus retusus (Coleoptera: Scolytidae) in a sawmill using pheromone-baited traps. Can. Entomol. 117: 49-55. Shore, T.L., J.A. McLean and J.C. Zanuncio. 1987. Reproduction and survival of the ambrosia beetle Trypodendron lineatum (Coleoptera: Scolytidae) in Douglas-fir and western hemlock logs. Can. Entornol. 119: 13 1-139. Shore, T.L. and J.A. McLean. 1988. The use of mark-recapture to evaluate a pheromone-based mass trapping program for ambrosia beetles in a sawmill. Can. J. For. Res. 18: 11131117. Stark R.W. K. Graham and D. Wood. 1985. Manual of Forest Insects and Damage. Supplementary Manual for FRST 308 University of British Columbia. 90 pp. Speight, M. and D. Wainhouse. 1989. Ecology and Management of Forest Insects. Clarendon Press, Oxford. 1989. 374 pp. Sweeney, J.D. and J.J. Turgeon. 1994. Life cycle and phenology of a cone maggot, Strobilomyla applachensis Michelsen. (Diptera: Anthomyiidae) on black spruce, Picea mariana (Mill.) B.S.P. in eastern Canada. Can. Entomol. 126: 49-59. Wagner, T.L., Hsin-I Wu, P.J. Sharpe and R.N. Coulson. 1984a. Modelling distributions of insect development time: A literature review and application of the Weibull ftinction. Ann. Entomol. Soc. Am. 77: 475-487. Wagner, T.L., Hsin-I Wu, P.J. Sharpe, R.M. Schoolfield and R.N. Coulson. 1984b. Modelling insect development rates: A literature review and application of a biophysical model. Ann. Entomol. Soc. Am. 77: 208-225. Welch, S.M., B.A. Croft and M.F. Michels. 1981. Environ. Entomol. 10: 425-432.  Validation of pest management models.  Worrall, J.G. and D. Elliott. 1990. Dendrology 111. U.B.C. Access Guided Independent Study. University of British Columbia, Vancouver B.C. Canada. Vol 2., 43-53 pp. Wood, S.L. and D.E. Bright. 1994. A Catalog of Scolytidae and Platypodidae (Coleoptera), Part 2: Taxonomic Index. Volume A. Number 13. Great Basin Naturalist Memoirs Brigham Young University. 833 pp. Zar, J.H. 1986. Biostatistical Analysis. Prentice-Hall, Inc., Englewood Cliffs, New Jersey 07632. p. 236-252.  Appendix 2-1. Randomization of treatments used in the 8 x 8 Latin square test conducted at the China Creek dry land sort near Port Alberni 1992.  114  Position Time  1  2  3  4  5  6  7  8  1  EP  L  LEP  LP  E  P  LE  CONT  2  LE  E  P  CONT  LP  EP  LEP  L  3  E  LEP  CONT  EP  P  L  LP  LE  4  LEP  LP  EP  L  CONT  LE  P  E  5  L  LE  LP  P  LEP  CONT  E  EP  6  P  CONT  LE  E  L  LEP  EP  LP  7  LP  P  L  LE  EP  E  CONT  LEP  8  CONT  EP  E  LEP  LE  LP  L  P  Appendix 2-2. Randomization of treatments used in the repeated 8 x 8 Latin square test conducted in the Foreshore Park area of the Pacific Spirit Park, Vancouver 1993. Position Time  1  2  3  4  5  6  7  8  1  EP  LEP  CONT  P  LP  E  LE  L  2  E  P  L  CONT  LE  LP  EP  LEP  3  LEP  E  LE  LP  CONT  P  L  EP  4  L  EP  LP  E  P  LEP  CONT  LE  5  LE  L  P  LEP  E  EP  LP  CONT  6  P  LP  EP  LE  L  CONT  LEP  E  7  LP  CONT  LEP  L  EP  LE  E  P  8  CONT  LE  E  EP  LEP  L  P  LP  113  APPENDICES  115  Appendix 3-1. Data sheet used to record numbers of each life stage during each dissection interval.  Date: July 1, 1993 Data for insect development at 18° C  Julian Date  Temp (Tmt)  Gallery Degree Niches Eggs (Rep) Stain*  182  18  1  182  18  2  182  18  3  182  18  4  182  18  5  182  18  6  182  18  7  182  18  8  182  18  9  182  18  10  *  Larvae Pupae Teneral Empty Notes Adults Niches  a = At least 1 body length (3mm) penetration into wood b = Presence offorking and/or lateral galleries c Galleries present and light brown stain d = Galleries present and heavy dark stain  o  CD  CD  II  II  II  C..  I  — *  -  -  II  Cl) CD  CD  0000  C)  Cl)  C) r.)  Cl)  C)  -  CA)  (71  Cl)  0)  I3 CA)  CD  CA)  0)  Cl)  C) —  Cl)  Cl) -  —‘  C)  C)  0  0  C) -I.  CA)  F)  -  CA)  (I) C) -L  CA)  ‘) -L  0)  C)  :  Cl)  -  C)  (7)  CA)  L  CA)  -4  CA) CO  m  CA)  Cl)  C)  (0 r..3  CO -  -  C)  C) CA)  ) CA)  CA)  O  C)  Ci)  Cl)  C) L  )  Ci) Cl)  Cl) L  -  C)  C) ) Ci)  Ci) C)  01  CO L  CA)  I)  Ci Cl)  C)  0) 1’)  L  r’)  1%)  CA)  CD  Ci)  Cl)  C)  -  0 CA)  0)  C)  -  ay qjo q ui suoss!p oqi noqno.np pasn oounbs uqdtu  911  z-c x!puddV  117  Appendix 3-3. Description of the Campbell Scientific CR10 datalogger used to collect meteorological data at the South Campus and to measure temperatures inside the logs. The CR10 datalogger makes voltage measurements by integrating the electrical input signal from sensors and then holding the integrated value for further analogue to digital conversion. There are two possible integration times: slow integration at 2.72 milliseconds, or fast integration at 250 microseconds; either can be programmed into the CR10 for voltage measurement instructions. Since one of the most common sources of “noise” and thus measurement error is 60 Hz from AC power lines,  a slow integration time was selected and the 7.5 mV 60 Hz rejection range  measurement sequence was pre-programmed into the unit.  Thermocouple temperature  measurements were referenced against that of the internal temperature of the control module using the 1OTCRT thermocouple reference (± 0.2°C) (Anon 1991). In the field and laboratory studies temperature measurements inside the bark and log were taken using Copper/Constantan thermocouple wires. All thermocouples used in these experiments were prepared in the lab.  Copper/Constantan wires were twisted together at the sensor end and  soldered together. To prevent oxidization, the sensor tip was further coated with epoxy resin.  All data were recorded and downloaded into the CR10 storage module. Once a week, the stored data were downloaded into a Zenith 386/SX portable computer in ‘comma delimited’ ASCII format. These files were subsequently imported into a Borland Quattro-Pro spreadsheet program for further analysis.  C  ‘2  W  19  (  l  <  Si)  .(  Si,  Si,  (  t  8  I.  I  9  10  56  11 2  I  I  1234  99  99  /IbDI  /  -d I (DC  N  C  1-  C  U)  C  Dl  >  0.0.00000000CC  III)cI)a)cocooI — —  iOOOOi  IaIHnad5th45I  000000000  9)  © CAMPBELL scENTIFIC  ©s.....1 \.. • •J  SERIAL I/O  WIRING PANEL  CRIOWP  Wiring diagram for the CR10 used to monitor the ambient treatment at the south campus location. Measurements were made under the bark and in the area of gallery construction inside the wood on the top, east, bottom, and west quadrants.  c#2G.rkYop)  c#3WoodWest)  c#4Brk(West)  J UI  I(I)(fl(I)(fl(fl(fl(E)(fl([)(F)(I)(flt  = .J..P b  = —  c#5Wood(Bottom)  —  c#6BarkBottom)  I  c#7Wood(East)  I  L C  Appendix 3-4. Program written for CR10 datalogger to monitor internal environmental chamber temperatures in 20, 25 and 30°C treatments.  119  Program: INTERNAL ENVIRONMENTAL CHAMBER TEMPERATURE Flag Usage: FllE NAME: OVENTEMP.DOC (10/05/93) Input Channel Usage: Excitation Channel Usage: Control Port Usage: Pulse Input Channel Usage: Output Array Definitions: This Program was written to monitor internal oven temperatures in each of the three ovens set up in the Laboratory. Oven temperatures were set at 20, 25, and 30 degrees Celsius.  *  1 01: 300  Table 1 Programs Sec. Execution Interval  01: P10 01: 6  Battery Voltage Loc [: BATTERY]  02: P17 01: 1  Module Temperature Loc[:CR1OTEMP]  03: P13 01:3 02: 22 03:7 04: 1 05: 1 06: 2 07: 1 08: 0  Thermocouple Temp (SE) Reps 7.5 mV 60 Hz rejection Range iNChan Type T (Copper-Constantan) Ref Temp Loc CR10 TEMP Loc [:OVENS 1-3] Mult Offset  04: P92 01: 0 02: 15 03: 10 05: P77 01: 110  If time is minutes into a minute interval Set high Flag 0 (output) Real Time Day,Hour-Minute  06: P71 01:4 02: 1  Average Reps Loc CR10 TEMP  120 07: P92 01: 0 02: 1440 03: 10  If time is minutes into a minute interval Set high Flag 0 (output)  08: P77 01: 100  Real Time Julian Day  09: P74 01:4 02: 0 03:1  Minimize Reps Value only LocCR1OTEMP  10: P73 01:4 02: 0 03: 1  Maximize Reps Value only Loc CR10 TEMP  11: P71 01:4 02: 1  Average Reps Loc CR10 TEMP  12: P82 01:4 02: 1  Standard Deviation Reps Sample Loc CR10 TEMP  13: P  End Table 1  Appendix 3-5. CR10 program to monitor temperature under the bark and inside the wood in the log (top, east, bottom, west) located at the South Campus.  121  Program: BARK AJ1D LOG INTERNAL TEMPERATURE SOUTH CAMPUS Flag Usage: FILE NAME: SCTHERM1 .DOC (10/05/93) Input Channel Usage: Excitation Channel Usage: Control Port Usage: Pulse Input Channel Usage: Output Array Definitions: -  This program was written to monitor the temperature under the bark and inside the wood at four locations in the log: (Top, Bottom, East and West) located in the South Campus, Vancouver B.C. 1993.  *Table 1 Programs 01: 300 Sec. Execution Interval 01: P10 01: 13  Battery Voltage Loc [:BATTERY  02: P11 01: 1 02:1 03: 3 04: 1 05: 1 06: 0  Temp 107 Probe Rep INChan Excite all reps w/EXchan 3 Loc [INTERNAL CR10 TEMPERATURE] Mult Offset  03: P11 01: 1 02:2 03: 1  Temp 107 Probe Rep INChan Excite all reps wfEXchan 1  04: 2 01: 1 02:4 03: 1 04: 2 05:3 06: 1 07: 0  I  RH 207 Probe Rep INChan Excite all reps wfEXchan 1 Temperature Loc RH THERM Loc[:%RHPROBE] Mult Offset  122 05: P13 01:8 02: 22 03:5 04: 1 05: 1 06: 4 07: 1 08: 0  Thermocouple Temp (SE) Reps 7.5 mV 60 Hz rejection Range INChan Type T (Copper-Constantan) Ref Temp Loc TNT TEMP Loc {:THERMOCOUPLE5 # 1-8] Mult Offset  06: P92 01: 0 02: 30 03: 10  If time is minutes into a minute interval Set high Flag 0 (output)  07: P77 01: 110  Real Time Day,Hour-Minute  08: P71 01: 13 02: 1  Average Reps Loc TNT TEMP  09: P92 01: 0 02: 1440 03: 10  If time is minutes into a minute interval Set high Flag 0 (output)  10: P77 01: 100  Real Time Julian Day  11: P74 01: 13 02: 0 03: 1  Minimize Reps Value only LocINT TEMP  12: P73 01: 13 02: 0 03: 1  Maximize Reps Value only LocINT TEMP  13: P71 01: 13 02: 1  Average Reps Loc TNT TEMP  14: P  End Table 1  Appendix 3-6. Modified CR10 program to measure bark and wood temperatures at all four quadrants including additional bark test thermocouple.  123  Program: THERMOCOUPLE POSITION TO MEASURE BARK TEMP Flag Usage: Fll.E NAME: SCTHERM2.DOC (09/06/93) Input Channel Usage: Excitation Channel Usage: Control Port Usage: Pulse Input Channel Usage: Output Array Definitions: This program was written to monitor the temperature under the bark and inside the wood in logs placed in the south campus summer 1993. The program was modified to include an extra thermocoulpe to compare two different thermocouple locations in the bark.  01: 300  Sec. Execution Interval  01: P10 01:P13  Battery Voltage Loc{:BATTERY]  02: P11 01: 1 02: 1 03: 3 04: 1 05: 1 06: 0  Temp 107 Probe Rep INChan Excite all reps wfEXchan 3 Loc [:INT TEMP J Mult Offset  03: P11 01: 1 02:2 03: 1 04: 2 05: 1 06: 0  Temp 107 Probe Rep INChan Excite all reps w/EXchan 1 Loc [:ATR TEMP] Mult Offset  04: P12 01: 1 02:4 03: 1 04: 2 05:3 06: 1 07: 0  RH2O7Probe Rep INChan Excite all reps wfEXchan 1 Temperature Loc AIR TEMP Loc[:RHPROBE] Mult Offset  124 05: P13 01: 1 02: 22 03:3 04: 1 05: 1 06: 4 07: 1 08: 0  Thermocouple Temp (SE) Rep 7.5 mV 60 Hz rejection Range iNChan Type T (Copper-Constantan) Ref Temp Loc TNT TEMP Loc [:BARK TEST] Mult Offset  06: P13 01: 8 02: 22 03:5 04: 1 05: 1 06: 5 07: 1 08: 0  Thermocouple Temp (SE) Reps 7.5 mV 60 Hz rejection Range iNChan Type T (Copper-Constantan) Ref Temp Loc INT TEMP Loc [:TC #1 8] BARK TEST Mult Offset  07: P92 01: 0 02: 30 03: 10  If time is minutes into a minute interval Set high Flag 0 (output)  08: P77 01:110  Real Time Day,Hour-Minute  09: P71 01: 13 02: 1  Average Reps Loc TNT TEMP  10: P92 01: 0 02: 1440 03: 10  If time is minutes into a minute interval Set high Flag 0 (output)  11: P77 01:100  Real Time Julian Day  12: P74 01: 13 02: 0 03: 1  Minimize Reps Value only Loc TNT TEMP  -  125  13: P73 01: 13 02: 0 03: 1  Maximize Reps Value only Loc INT TEMP  14: P71 01: 13 02: 1  Average Reps 1NT TEMP  15: P EndTablel  126 Appendix 3-7. Detailed summary sheets of absolute, proportional and cumulative numbers of each life stage present at each measurement interval. Absolute 1993 brood development at  18°  C.  Larvae JD 133*  #Days  Galleries  Niches Eggs  139 143 149 153 159 163 169 173 179 183 189 193 199 203 209 213 219 223 229 233 239 243  0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110  0 16 14 9 11 13 16 13 14 17 17 14 16 13 10 21 2  0 23 60 51 109 111 101 77 58 71 61 38 25 15 0 2 0  0 20 47 7 11 3 6 3 0  Total  110  216  802  97  *  =  Estimated date of attack in Pemberton  Li  L2  Teneral  Empty  Adults  Niches  Total  Pupae  0 36 18 41 13 7 10 0  0 1 0 14 46 74 69 50 47 17 1 2 0  0 4 ii 31 42 57 71 84 72 185 19  125  321  576  0 5 38 47 13 14 0 0 0 1 0  0 3 50 59 63 20 ii 1 7 0  0 5 41 97 72 77 20 11 1 8 0  118  214  332  127  Proportion (total per gallery) 1993 brood development at 18° C. Larvae ID  #Days  133 139 143 149 153 159 163 169 173 179 183 189 193 199 203 209 213 219 223 229 233 239 243  0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110  0 16 14 9 11 13 16 13 14 17 17 14 16 13 10 21 2  0.00 1.44 4.29 5.67 9.91 8.54 6.31 5.92 4.14 4.18 3.59 2.71 1.56 1.15 0.00 0.10 0.00  0.00 1.25 3.36 0.78 1.00 0.23 0.38 0.23 0.00  Total  110  216  59.51  7.22  Galleries  Niches Eggs  Li  Teneral  Empty Niches  L2  Total  Pupae  Adults  0.00 0.36 4.22 4.27 1.00 0.88 0.00 0.00 0.00 0.06 0.00  0.00 0.33 4.55 4.54 3.94 1.54 0.79 0.06 0.41 0.00  0.00 0.36 4.55 8.82 5.54 4.81 1.54 0.79 0.06 0.47 0.00  0.00 2.77 1.13 3.15 0.93 0.41 0.59 0.00  0.00 0.08 0.00 1.08 3.29 4.35 4.06 3.57 2.94 1.31 0.10 0.10 0.00  0.00 0.31 0.79 1.82 2.47 4.07 4.44 6.46 7.20 8.81 9.50  10.79  16.15  26.94  8.98  20.86  45.87  128 Cumulative 1993 brood development at 18° C. Larvae JD  #Days  133 139 143 149 153 159 163 169 173 179 183 189 193 199 203 209 213 219 223 229 233 239 243 Total  Galleries  Niches  0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110  0 16 30 39 50 63 79 92 106 123 140 154 170 183 193 214 216  0 23 83 134 243 354 455 532 590 661 722 760 785 800 800 802 802  0 20 67 74 85 88 94 97  110  216  802  97  Eggs  Li  L2  0 5 43 90 103 117 117 117 117 118  0 3 53 112 175 195 206 207 214  118  214  Total  0 5 46 143 215 292 312 323 324 332 332 332  332  Pupae  Teneral  Empty  Adults  Niches  0 36 54 95 108 115 125  0 1 1 15 61 135 204 254 301 318 319 321  125  321  0 4 15 46 88 145 216 300 372 557 576 576  129  1993 brood development at 200 C. Absolute Counts ID 137 142 147 152 157 162 167 172 177 182 187 Total  #Days 0 5 10 15 20 25 30 35 40 45 50 50  Galleries 0 10 10 11 7 10 10 11 8 5 3 85  Niches  Eggs  Li  0 32 24 47 32 45 13 0 6 199  0 13 1 2 1 0  0 15 9 16 4 1 0  17  45  Proportional Counts/Gallery JD 137 142 147 152 157 162 167 172 177 182 187 Total  #Days 0 5 10 15 20 25 30 35 40 45 50 50  Galleries 0 10 10 ii 7 10 10 11 8 5 3 85  #Days 0 5 10 15 20 25 30 35 40 45 50 50  Galleries 0 10 20 31 38 48 58 69 77 5 3 85  0 5 13 5 6 0 1 0 30  0 15 14 29 9 7 0 1 0 75  Larvae L2 Total  Niches  Eggs  Li  0.00 2.91 3.43 4.70 3.20 4.09 1.63 0.00 2.00 21.96  0.00 1.20 0.14 0.20 0.10 0.00  0.00 1.36 1.29 1.60 0.40 0.09 0.00  1.64  4.74  0.00 0.71 1.30 0.50 0.55 0.00 0.20 0.00 3.26  Li  Larvae L2 Total  Cumulative Counts JD 137 142 147 152 157 162 167 172 177 182 187 Total  Larvae L2 Total  Niches  Eggs  0 32 56 103 135 180 193 193 199 199  0 13 14 16 17  0 15 24 40 44 45  17  45  1.36 2.00 2.90 0.90 0.64 0.00 0.20 0.00 8.00  Teneral Pupae  0 18 8 8 1 0 35  Pupae  0.00 1.80 0.80 0.73 0.13 0.00 3.46  Pupae  0 5 18 23 29 29 30  0 15 29 58 67 74 74 75  0 18 26 34 35 0  30  75  35  Adults  Empty Niches  0 1 0 8 14 19 7 1 50  0 2 0 8 16 13 3 6 48  Teneral Adults  Empty Niches  0.00 0.14 0.00 0.80 1.27 2.38 1.40 0.33 6.32  0.00 0.29 0.00 0.80 1.45 1.63 0.60 2.00 6.77  Teneral  Empty  Adults  Niches  0 1 1 9 23 42 49 50 50  0 2 2 10 26 39 42 48 48  130  1993 brood development at 25° C. Absolute Counts JD 127 132 137 142 147 152 157 162 167 172 177 182 Total  #Days 0 5 10 15 20 25 30 35 40 45 50 55 55  Galleries 0 4 7 8 9 9 8 18 21 22 13 3 122  Niches  Eggs  0 6 26 27 48 55 19 43 7 12 0 243  0 4 17 12 8 0  41  Li 0 5 14 9 5 1 0  34  Proportional Counts/Gallery JD 127 132 137 142 147 152 157 162 167 172 177 182 Total  /lDays 0 5 10 15 20 25 30 35 40 45 50 55 55  Galleries 0 4 7 8 9 9 8 18 21 22 13 3 122  Cumulative Counts JD #Days Galleries 127 0 0 132 5 4 137 10 11 142 15 19 147 20 28 152 25 37 157 30 45 162 35 63 167 40 84 172 45 106 50 177 119 182 55 122 Total 55 122  Niches  Eggs  0.00 0.86 3.25 3.00 5.33 6.88 1.06 2.05 0.32 0.92 0.00 23.67  0.00 0.57 2.13 1.33 0.89 0.00  4.92  Niches  Eggs  0 6 32 59 107 162 181 224 231 243 243 243  0 4 21 33 41  41  Li 0.00 0.63 1.56 1.00 0.63 0.06 0.00  Larvae L2 Total  0 5 13 5 6 0 1 0 27  0 5 15 30 8 2 1 0 61  Larvae L2 Total  Pupae  0 3 15 3 0  21  Pupae  Teneral Adults  Empty Niches  0 20 44 47 45 52 1 209  0 17 46 42 51 72 3 231  Teneral Adults  Empty Niches  0.00 2.13 2.56 2.00 2.32 5.54 1.00 15.54  0.00 0.11 2.33 0.38 0.06 0.05 0.00  0.63 1.67 3.33 1.10 0.12 0.05 0.00  0.00 0.33 1.88 0.17 0.00  3.88  2.93  6.90  2.38  0.00 2.50 2.44 2.24 2.05 4.00 0.33 13.56  Li  Larvae L2 Total  Pupae  Teneral Adults  Empty Niches  0 20 64 111 156 208 209 209  17 63 105 156 228 231 231  0 5 19 28 33 34  34  0 1 22 25 26 27  0 5 20 50 58 60 61  27  61  0 3 18 21  21  131  Absolute 1993 brood development at 300 C. Larvae ID 133*  #Days  Galleries  Niches  Eggs  Li  138 142 148 152 158 162 168 172 178 182 188 192 198 202 208  0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75  0 23 21 10 16 12 7 12 8 7  0 32 73 65 23 56 36 29 17 0  0 33 22 15 2 0  0 30 30 9 0  Total  75  116  331  72  69  *  =  Estimated date of attack in Pemberton  L2  Teneral Empty Total  Pupae  0 7 11 19 25 7 0  0 30 37 20 19 25 7 0  0 1 10 13 4 1  69  138  29  Adults Niches  0 10 11 41 21 0  0 5 11 44 37 32  83  129  Proportional 1993 brood development at  300  C. Teneral  Empty  Pupae  Adults  Niches  0.00 0.06 0.83 1.57 3.42 2.63 0.00  0.00 0.83 1.57 3.42 2.63 0.00  0.00 0.09 0.31 1.52 2.18 0.00  8.51  8.45  4.10  Larvae ID 133*  #Days  Galleries  Niches  Eggs  Li  138 142 148 152 158 162 168 172 178 182 188 192 198 202 208  0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75  0 23 21 10 16 12 7 12 8 7  0.00 1.39 3.48 6.50 1.44 4.67 5.14 2.42 2.13 0.00  0.00 1.43 1.05 1.50 0.13 0.00  0.00 1.43 3.00 0.56 0.00  Total  75  116  27.17  4.11  4.99  *  =  Estimated date of attack in Pemberton  L2  Total  0.00 0.70 0.69 1.58 3.57 0.58 0.00  0.00 1.43 3.70 1.25 1.58 3.57 0.58 0.00  7.12  12.11  132  133 Cumulative 1993 brood development at 30° C. Larvae ID 133*  #Days  Galleries  Niches  Eggs  Li  138 142 148 152 158 162 168 172 178 182 188 192 198 202 208  0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75  0 23 21 10 16 12 7 12 8 7  0 32 105 170 193 249 285 314 331 331  0 33 55 70 72 72  0 30 60 69 69  Total  75  116  331  72  69  *  Estimated date of attack in Pemberton  L2  Total  Pupae  0 7 18 37 62 69 69  0 30 67 87 106 131 138 138  0 1 11 24 28 29  69  138  29  Teneral  Empty  Adults  Niches  0 10 21 62 83 0  0 5 16 60 97 129  83  129  AIR TEMP  11.19 16.14 12.82 17.10 13.95  16.13 21.22 20.46 19.46 19.90 21.59 23.31 29.11 24.79 21.86 15.49 18.94 21.88 25.80 23.21 22.93 25.11 20.99 22.72 21.47 15.87  CR10 TEMP  14.32 14.12 13.24 14.48 13.82  18.14 19.63 18.39 16.66 19.02 21.12 21.16 21.79 21.46 20.09 18.15 19.53 20.37 23.13 22.23 23.07 23.02 21.75 21.66 20.88 19.69  J.D.  Mayl2l 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151  29.50 31.75 28.11 24.03 36.50 38.86 35.97 39.62 38.32 35.39 19.60 37.74 32.63 38.26 40.71 41.78 42.21 36.22 39.24 36.47 19.69 19.60 21.74 20.04 18.49 22.69 25.12 24.35 26.64 25.65 23.49 16.52 23.49 22.50 26.16 28.37 27.28 27.35 24.53 24.86 23.45 17.74 18.16 21.21 19.50 17.84 21.67 23.91 23.00 25.61 24.40 21.97 15.90 21.55 21.81 25.50 25.77 25.84 26.48 23.45 24.19 22.88 18.16  15.74 17.95 16.57 15.62 17.50 19.25 19.29 21.17 20.44 18.49 14.88 17.31 18.05 20.78 19.83 20.11 21.26 19.20 19.22 19.43 16.73 15.51 17.63 16.32 15.44 17.23 19.04 18.94 20.67 20.09 18.15 15.03 17.03 17.79 20.44 19.46 19.81 20.82 18.96 18.93 19.13 16.83 26.59 31.26 25.93 19.77 29.93 34.39 31.47 31.07 30.83 24.10 16.19 34.19 34.17 35.44 29.88 36.19 32.21 30.31 33.37 31.33 19.30  29.50 31.75 28.11 24.03 36.50 38.86 35.97 39.62 38.32 35.39 19.60 37.74 32.63 38.26 40.71 41.78 42.21 36.22 39.24 36.47 19.69 27.82 30.32 25.06 22.66 34.01 36.40 34.02 37.33 35.27 32.20 18.37 35.06 31.14 35.44 38.63 39.46 40.18 34.74 35.95 34.60 20.48  99.00 99.00 99.60 101.30 101.00 100.40 99.90 91.00 100.60 101.00 101.40 101.40 100.60 91.50 83.80 94.80 101.00 101.50 101.80 101.10 101.30  27.85 33.30 27.76 21.05 31.85 36.65 33.80 33.61 33.56 24.91 16.64 36.80 36.89 37.98 30.84 37.99 34.02 32.30 36.02 33.25 18.56  13.28 30.83 14.47 29.35 18.67  12.28 18.29 12.06 18.07 14.46 12.88 17.14 11.84 17.31 14.19  11.03 13.59 11.04 14.09 12.52  11.18 13.19 10.89 13.59 12.40  12.78 23.19 12.17 23.10 14.75  13.28 30.83 14.47 29.35 18.67  14.12 28.31 13.97 26.28 17.93  101.50 101.00 100.80 103.10 101.90  12.08 25.01 12.30 25.06 14.76  BARK ORIG  TC#8  TC#6  TC#7  -  TC#5  TC#4  TC#3  BARK TEST  TC#2  RH%  TC#1  -  South Campus Log Total Summary Data 1993. Daily MAXIMUM BARK NEW  o  CD  -l  CD  CD  -4  C  CD  )  CD  CD  f4•  c#  CDp  -CD CD  CDCD  -  00  I  CR10 TEMP  20.44 18.79 21.14 19.56 21.31 19.97 18.47 17.94 17.10 16.80 16.93 20.06 18.28 17.27 20.49 20.52 22.33 23.63 22.10 21.51 20.01 16.97 19.38 19.16 23.02 21.47 21.53 18.93 21.64 20.48  J.D.  Junel52 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 20.70 17.84 22.47 17.67 22.13 20.72 18.75 20.16 17.94 18.87 17.58 22.18 18.11 16.95 20.20 20.89 23.88 24.22 21.61 20.71 19.60 18.03 20.51 19.64 24.61 22.17 21.49 19.32 22.05 22.34  AIR TEMP 101.20 100.80 90.30 100.30 101.00 100.10 98.10 89.10 100.70 100.90 101.20 98.20 101.30 100.60 100.80 100.20 101.00 89.20 98.10 99.10 100.60 98.30 90.80 89.30 95.20 98.70 98.00 97.70 99.00 95.80  RH%  21.00 19.41 21.18 19.83 18.32 17.79 16.94 24.68 20.59 25.22 20.32 16.61 23.76 28.88 27.68 39.74 39.70 37.51 24.28 33.34 35.06 33.37 42.08 28.62 37.47 33.52 40.88 36.18  BARK TEST 33.54 27.41 37.91 29.51 31.33 27.62 27.77 32.63 21.30 16.65 16.78 19.92 18.13 17.12 20.34 20.41 22.22 39.61 39.18 37.46 24.31 33.88 34.73 33.63 41.47 29.13 38.23 34.07 40.86 36.58  TC#1  -  35.74 30.77 40.26 31.46 32.60 30.08 29.41 34.87 24.96 33.32 29.34 36.39 26.10 18.29 34.23 39.58 39.38 41.86 42.22 40.58 26.96 36.58 37.68 35.83 45.09 31.25 41.80 37.80 44.44 40.55  TC#2  33.62 21.84 33.97 22.71 33.14 21.73 25.84 25.69 22.64 36.53 32.71 40.15 27.61 18.79 37.60 43.10 42.28 36.37 36.91 32.33 26.03 26.76 34.37 27.85 37.97 26.15 34.95 26.88 35.79 29.26  TC#3  35.91 22.38 37.08 22.80 35.62 22.42 28.21 28.11 26.07 22.60 21.74 33.97 21.25 16.78 34.11 29.61 36.67 38.97 39.54 34.68 30.07 28.60 3844 29.17 40.90 28.19 37.77 28.74 38.73 31.71  TC#4  17.77 16.15 19.45 17.06 19.04 17.84 16.30 17.02 15.13 24.18 23.35 36.75 22.11 16.64 36.70 32.64 39.60 22.69 21.52 20.54 17.12 16.87 19.24 18.42 22.74 20.31 20.27 18.00 21.11 20.06  TC#5  18.05 16.37 19.84 17.25 19.48 18.05 16.67 17.54 15.47 15.73 15.53 18.65 16.09 15.56 18.56 19.58 20.74 23.11 22.03 21.07 17.61 17.48 19.66 18.74 23.08 20.61 20.52 18.54 21.37 20.65  TC#6  -  22.26 19.75 25.64 20.45 23.38 21.24 19.79 21.60 16.84 16.30 15.88 19.04 16.28 15.66 18.84 19.93 21.18 26.80 25.99 24.94 18.21 20.84 22.82 23.04 27.70 23.53 24.55 22.57 27.13 25.44  TC#7  23.01 21.14 26.58 21.97 24.31 22.42 20.66 22.47 17.66 21.75 19.43 24.51 19.60 16.88 22.59 26.46 26.16 27.34 28.29 27.10 19.13 23.42 24.21 24.04 30.16 24.00 27.13 24.54 29.91 26.41  TC#8  35.74 30.77 40.26 31.46 32.60 30.08 29.41 34.87 24.96 33.32 29.34 36.39 26.10 18.29 34.23 39.58 39.38 41.86 42.22 40.58 26.96 36.58 37.68 35.83 45.09 31.25 41.80 37.80 44.44 40.55  BARK ORIG  South Campus Log Total Summary Data 1993. Daily MAXIMUM  21.00 19.41 21.18 19.83 18.32 17.79 16.94 24.68 20.59 25.22 20.32 16.61 23.76 28.88 27.68 39.74 39.70 37.51 24.28 33.34 35.06 33.37 42.08 28.62 37.47 33.52 40.88 36.18  BARK NEW  CR10 TEMP  19.66 21.56 20.37 22.34 21.92 21.26 22.30 22.43 21.91 21.61 20.17 20.47 21.70 21.75 20.23 21.08 22.28 23.58 21.51 20.19 18.71 18.11 19.96 21.44 22.97 23.24 22.08 21.01 19.09 18.15 22.40  J.D.  Julyl 82 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 19.47 21.54 20.89 21.73 21.04 20.43 22.63 20.32 21.80 21.98 19.15 22.57 21.68 21.18 17.59 20.70 23.24 22.33 21.37 17.32 22.34 20.90 20.73 21.66 22.35 23.36 25.85 20.27 19.79 20.97 23.25  AIR TEMP 97.80 100.30 100.10 100.80 99.60 99.90 100.60 100.50 100.10 92.00 100.80 98.10 97.30 100.20 99.70 100.20 100.90 99.80 100.30 99.50 99.20 99.00 99.10 97.90 99.70 100.10 96.60 99.90 100.20 100.00 98.60  RH%  23.54 36.82 27.48 37.66 37.64 33.70 39.85 37.56 37.42 34.36 34.59 37.16 39.43 34.01 20.44 36.18 40.77 42.67 37.56 21.89 28.63 23.34 33.63 40.22 40.19 41.04 32.20 26.73 27.33 31.77 38.84  BARK TEST 24.19 36.66 2810 37.78 36.98 32.86 38.48 36.99 36.11 33.33 34.45 36.26 38.28 33.51 20.66 35.65 39.08 40.88 36.09 21.26 28.27 23.00 33.12 38.88 38.53 39.27 31.87 27.11 26.92 31.54 37.94  TC#1  -  25.60 40.14 30.86 41.48 40.34 37.05 42.08 40.35 39.47 37.00 37.92 40.26 41.80 36.32 22.74 39.23 42.22 44.24 40.50 22.40 30.92 24.83 36.13 42.23 42.46 43.00 35.66 29.72 34.01 38.07 41.85  TC#2  23.66 35.56 30.48 38.82 37.46 36.18 38.67 37.72 35.74 33.66 29.45 32.03 35.42 35.04 18.31 36.41 37.70 39.76 25.53 19.14 28.27 24.36 31.34 37.72 39.79 38.17 31.41 22.36 17.93 23.35 38.09  TC#3  26.19 38.79 33.93 41.83 40.02 39.09 41.51 40.17 37.69 36.92 31.92 34.66 38.06 37.89 18.57 39.03 40.55 42.29 26.11 19.72 31.97 27.95 35.64 41.07 42.66 41.61 35.60 23.10 19.62 24.54 40.64  TC#4  17.38 20.59 18.80 21.17 20.63 19.84 20.96 20.83 20.37 20.45 18.21 19.51 2043 20.38 16.68 19.50 20.94 21.68 19.57 16.92 17.98 17.57 18.69 20.65 21.47 21.80 21.13 18.63 16.18 17.03 20.88  TC#5  17.65 20.92 19.14 21.38 20.75 20.02 21.07 20.93 20.57 20.66 18.50 19.72 20.63 20.51 16.39 19.65 21.24 21.83 19.91 16.72 18.41 17.94 18.98 20.87 21.64 22.12 21.65 18.83 16.83 17.30 21.03  TC#6  -  19.80 24.76 21.17 25.36 24.69 23.02 25.50 25.15 24.58 24.94 21.44 23.96 25.69 23.81 18.00 23.09 26.16 27.98 25.73 18.50 21.11 19.37 22.32 25.10 25.55 26.40 24.14 21.26 20.47 22.50 25.39  TC#7  20.31 25.88 22.13 27.36 25.55 23.71 27.90 27.84 25.20 26.43 22.51 25.15 28.09 25.05 18.79 24.89 29.20 30.71 28.10 19.08 22.09 20.24 23.81 26.48 28.22 29.21 25.50 22.59 23.39 25.31 28.26  TC#8  25.60 40.14 30.86 41.48 40.34 37.05 42.08 40.35 39.47 37.00 37.92 40.26 41.80 36.32 22.74 39.23 42.22 44.24 40.50 22.40 30.92 24.83 36.13 42.23 42.46 43.00 35.66 29.72 34.01 38.07 41.85  BARK ORIG  South Campus Log Total Summary Data 1993. Daily MAXIMUM  23.54 36.82 27.48 37.66 37.64 33.70 39.85 37.56 37.42 34.36 34.59 37.16 39.43 34.01 20.44 36.18 40.77 42.67 37.56 21.89 28.63 23.34 33.63 40.22 40.19 41.04 32.20 26.73 27.33 31.77 38.84  BARK NEW  C.,  CR10 TEMP  24.19 25.28 26.72 28.30 28.36 26.32 24.53 22.87 21.21 21.41 23.17 22.15 20.98 18.96 19.38 18.97 21.55 22.72 23.85 23.68 22.42 18.79 20.09 18.71 19.43 18.55 20.17  J.D.  Aug213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 24.45 24.97 28.63 32.78 29.93 23.63 23.45 22.46 18.72 21.39 23.54 22.18 21.13 18.46 21.87 19.22 22.86 23.13 24.47 26.97 18.57 23.09 20.62 18.95 19.62 19.64 20.34  AIR TEMP 100.00 99.30 98.40 88.50 92.30 99.60 99.30 91.70 99.80 100.20 99.70 99.80 99.00 99.20 99.40 99.30 99.20 99.80 99.10 99.30 96.20 98.90 98.40 89.20 100.40 100.60 99.60  RH%  37.37 38.66 41.39 45.19 4540 40.58 40.83 33.11 22.80 34.32 37.99 40.08 30.92 26.12 39.29 22.31 36.36 35.58 36.48 40.65 23.55 27.19 33.72 33.07 34.10 32.63 35.94  BARK TEST 36.09 36.24 40.05 43.83 44.13 40.48 39.70 33.55 22.26 34.46 36.54 38.24 31.16 25.56 38.60 22.02 35.61 34.51 34.90 38.55 2343 26.46 33.43 32.01 32.41 31.14 34.79  TC#1  -  41.25 39.38 44.27 47.01 47.51 44.45 43.83 36.33 24.02 37.72 40.36 41.97 35.04 29.39 44.25 23.39 38.64 38.09 38.66 42.68 25.79 30.14 38.00 35.88 36.83 37.23 39.25  TC#2  40.12 40.51 41.77 44.81 44.28 39.95 39.06 29.21 19.61 33.86 39.38 32.31 23.85 25.22 25.51 20.18 36.92 36.27 37.12 36.19 20.14 22.84 31.37 32.93 34.43 26.85 33.66  TC#3  42.65 43.41 44.51 47.55 47.12 42.72 41.83 30.87 20.53 37.46 42.46 35.72 24.98 27.91 26.83 21.31 39.45 38.92 39.15 39.31 20.89 24.52 33.60 36.27 37.25 29.04 36.85  TC#4  22.40 23.15 25.22 26.59 25.74 23.42 22.19 20.75 18.01 19.37 20.99 20.59 18.78 17.50 19.85 17.89 21.08 21.90 23.00 23.43 17.88 18.74 18.89 18.08 18.28 17.80 19.21  TC#5  22.57 23.33 25.53 27.03 25.94 23.47 22.42 20.93 17.91 19.72 21.29 20.79 19.18 17.72 20.44 18.04 21.38 22.23 23.20 23.87 17.48 19.18 19.27 18.36 18.51 18.10 19.35  TC#6  -  26.35 26.65 29.21 31.83 31.19 28.77 27.62 25.18 19.49 23.20 25.58 26.50 23.37 19.79 26.00 19.22 24.16 25.33 25.66 27.42 19.34 21.30 22.16 21.31 22.51 22.62 25.41  TC#7  29.10 29.03 31.23 33.88 34.07 31.95 30.25 26.31 19.95 25.57 28.64 29.61 24.93 20.80 28.76 19.81 25.35 28.18 28.49 30.47 20.13 22.84 24.23 23.48 25.66 25.42 28.61  TC#8  41.25 39.38 44.27 47.01 47.51 44.45 43.83 36.33 24.02 37.72 40.36 41.97 35.04 29.39 44.25 23.39 38.64 38.09 38.66 42.68 25.79 30.14 38.00 35.88 36.83 37.23 39.25  BARK ORIG  South Campus Log Total Summary Data 1993. Daily MAXIMUM  37.37 38.66 41.39 45.19 45.40 40.58 40.83 33.11 22.80 34.32 37.99 40.08 30.92 26.12 39.29 22.31 36.36 35.58 36.48 40.65 23.55 27.19 33.72 33.07 34.10 32.63 35.94  BARK NEW  May  121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151  J.D.  7.16 6.84 7.32 6.89 9.02  11.88 10.99 11.47 10.46 10.25 9.78 10.45 12.80 14.03 12.30 11.12 10.41 9.43 12.19 13.83 13.90 12.88 13.16 12.31 12.21 13.23  14.39 13.44 15.91 14.23 14.02 14.91 16.11 17.41 18.64 17.95 15.63 14.42 14.43 16.27 18.45 18.64 18.22 18.95 17.55 17.05 16.86  AIR TEMP  11.09 10.00 10.95 10.22 12.33  CR10 TEMP  86.90 66.61 68.70 75.80 62.84 58.47 61.15 36.56 64.50 65.60 90.30 67.03 53.19 41.00 57.00 60.81 64.35 74.90 59.55 74.80 88.40  78.50 47.60 77.20 65.13 82.90  RH% BARK TEST  14.38 10.80 12.40 10.71 10.11 11.18 12.41 13.43 15.82 13.91 12.50 10.81 10.52 11.77 14.64 14.97 15.08 15.67 14.00 14.95 14.23  7.21 5.90 8.62 6.81 10.96  TC#1  -  13.34 10.42 11.83 10.09 9.59 10.53 11.65 12.76 15.30 13.32 11.95 10.56 9.76 11.18 13.99 14.37 14.46 15.16 13.55 14.54 13.80  6.45 5.59 7.99 6.19 10.48  TC#2  13.91 11.18 13.07 11.51 10.97 12.06 13.24 14.16 15.97 13.94 12.50 11.06 11.39 12.90 15.22 15.27 15.43 15.39 13.65 14.84 14.18  7.91 6.67 8.50 7.53 10.66  TC#3  13.79 10.97 12.70 11.17 10.79 11.67 12.70 13.79 15.65 13.49 12.10 10.95 10.96 12.52 14.85 14.96 14.97 14.98 13.23 14.45 13.85  7.51 6.51 8.34 7.38 10.33  TC#4  12.91 11.57 13.48 12.15 11.84 12.08 13.16 14.39 15.90 14.89 13.14 11.99 11.92 13.15 14.97 15.49 15.07 15.82 14.25 14.70 14.61  8.72 7.72 8.60 8.56 10.78  TC#5  12.95 11.45 13.33 12.04 11.76 11.90 12.93 14.21 15.77 14.76 12.99 11.94 11.75 13.01 14.84 15.38 14.88 15.71 14.13 14.58 14.53  8.54 7.54 8.58 8.49 10.68  TC#6  -  13.84 11.60 13.52 12.03 11.77 12.53 13.71 14.76 16.62 14.38 12.87 11.51 11.82 13.30 15.71 15.96 15.82 15.72 14.25 14.80 14.48  8.39 7.19 8.87 8.18 10.78  TC#7  13.24 11.31 13.09 11.68 11.47 12.05 13.15 14.32 16.22 13.94 12.45 11.31 11.32 12.91 15.36 15.48 15.36 15.33 13.80 14.48 14.18  7.91 6.93 8.59 7.93 10.43  TC#8  13.34 10.42 11.83 10.09 9.59 10.53 11.65 12.76 15.30 13.32 11.95 10.56 9.76 11.18 13.99 14.37 14.46 15.16 13.55 14.54 13.80  6.45 5.59 7.99 6.19 10.48  BARK ORIG  South Campus Log Total Summary Data 1993. Daily MINIMUM  00  BARK NEW  June  CR10 TEMP  15.64 16.45 17.74 17.12 16.22 17.96 15.62 15.29 14.98 13.93 13.68 14.83 14.88 16.51 15.85 17.22 17.13 21.36 18.06 17.25 16.83 14.52 14.01 16.33 17.46 18.73 17.42 16.63 16.77 17.79  J.D.  152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 10.91 12.04 13.78 12.99 12.28 14.03 12.41 11.95 9.83 9.40 8.74 10.55 8.32 13.58 12.95 13.78 11.72 15.29 11.83 11.01 10.02 9.39 11.66 12.29 14.64 13.57 11.46 13.72 12.21 12.07  AIR TEMP 69.68 89.30 65.76 89.60 74.40 79.90 71.90 59.09 79.10 64.10 72.60 57.47 71.70 89.90 77.60 81.00 65.60 68.34 58.33 62.20 67.03 63.23 58.90 58.03 59.43 75.70 60.47 70.80 59.06 67.04  RH%  17.60 16.60 15.56 18.03 15.52 15.14 14.63 12.21 10.99 12.46 11.55 14.71 13.56 15.34 14.37 0.00 15.22 13.58 12.56 10.01 11.53 14.64 17.26 16.25 13.20 17.82 14.58 15.08  BARK TEST 10.97 14.20 20.27 15.75 12.29 15.00 13.09 12.81 11.65 13.78 13.53 14.65 14.73 16.21 14.70 17.02 16.20 0.00 15.22 13.38 12.50 10.18 11.51 14.77 17.31 16.14 13.31 17.77 14.55 15.03  TC#1  -  10.45 13.80 19.18 15.29 11.68 14.37 12.77 12.06 10.58 11.61 10.19 12.11 10.95 15.01 13.64 16.18 13.84 0.00 14.37 12.45 11.63 9.47 10.88 14.13 16.99 15.25 12.51 17.03 13.60 13.90  TC#2  11.72 14.65 18.58 15.43 13.05 15.61 13.08 13.08 12.08 11.67 9.49 11.66 10.16 14.66 13.41 15.71 13.05 0.00 15.08 13.72 13.23 11.01 11.82 14.38 16.53 16.11 13.53 16.63 14.60 14.85  TC#3  11.40 14.34 18.10 14.96 12.72 14.97 12.85 12.62 11.66 11.86 10.64 12.19 11.70 14.81 13.60 15.90 14.19 0.00 14.50 12.99 12.55 10.60 11.55 13.91 16.16 15.32 12.97 16.49 13.96 14.22  TC#4  12.91 14.13 15.86 15.31 13.87 15.58 13.83 13.36 12.27 12.24 10.14 11.81 10.96 14.47 13.37 15.39 13.55 0.00 15.11 13.75 13.15 11.56 12.40 13.88 15.71 15.57 14.50 14.74 14.56 14.92  TC#5  12.77 14.03 16.16 15.22 13.74 15.46 13.75 13.18 12.06 11.59 11.12 12.35 11.69 14.56 14.03 15.11 14.39 0.00 14.94 13.54 12.95 11.45 12.33 13.77 15.63 15.28 14.34 14.82 14.43 14.77  TC#6  -  12.32 14.38 18.39 15.49 13.78 15.69 13.21 13.41 12.27 11.71 10.94 12.24 11.45 14.45 13.95 14.99 14.17 0.00 15.87 14.26 13.01 11.23 12.49 14.52 16.63 16.55 14.19 16.35 15.10 15.68  TC#7  11.90 14.09 17.70 15.09 13.37 15.09 12.87 12.95 11.62 11.96 11.52 12.84 12.24 14.96 13.80 15.68 14.98 0.00 15.26 13.57 12.40 10.82 12.13 14.08 16.31 15.87 13.55 16.39 14.52 15.02  TC#8  10.45 13.80 19.18 15.29 11.68 14.37 12.77 12.06 10.58 11.61 10.19 12.11 10.95 15.01 13.64 16.18 13.84 0.00 14.37 12.45 11.63 9.47 10.88 14.13 16.99 15.25 12.51 17.03 13.60 13.90  BARK ORIG  South Campus Log Total Summary Data 1993. Daily MINIMUM  17.60 16.60 15.56 18.03 15.52 15.14 14.63 12.21 10.99 12.46 11.55 14.71 13.56 15.34 14.37 0.00 15.22 13.58 12.56 10.01 11.53 14.64 17.26 16.25 13.20 17.82 14.58 15.08  BARK NEW  July  182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212  J.D.  17.18 16.27 17.72 16.76 17.15 16.78 16.65 17.15 17.41 18.05 17.53 17.14 17.64 18.38 17.38 16.31 16.80 18.89 18.25 17.55 16.23 16.78 16.72 17.25 17.48 17.90 19.46 19.09 16.67 15.45 16.56  CR10 TEMP 12.33 12.32 13.22 12.52 10.76 11.27 10.73 12.32 11.35 13.35 12.27 13.59 13.97 13.57 12.71 12.30 11.80 13.80 12.19 13.49 12.36 13.65 13.65 12.84 11.75 11.58 14.27 14.35 11.88 11.44 13.59  AIR TEMP 72.40 70.20 78.80 67.69 67.81 67.12 62.53 73.00 70.20 67.97 80.00 72.40 70.70 75.60 83.90 73.40 67.52 66.01 84.20 92.70 64.32 87.40 72.80 69.94 73.90 69.49 64.12 89.80 85.70 70.20 63.41  RH%  13.67 13.15 15.73 13.37 12.35 12.71 11.61 13.52 12.09 14.35 13.74 14.19 16.04 16.32 13.88 13.06 13.13 16.85 13.72 14.88 13.03 14.24 14.17 14.38 13.41 12.80 14.95 15.83 12.43 10.44 14.57  BARK TEST 13.59 13.25 15.73 13.79 12.74 13.10 12.05 14.05 12.56 14.90 14.38 14.64 16.41 16.91 14.51 13.18 13.65 17.34 14.46 15.33 13.22 14.55 14.39 15.08 14.11 13.54 15.41 16.38 12.93 10.80 14.84  TC#1  -  12.70 12.71 15.19 12.85 11.55 12.13 11.05 13.09 11.37 13.91 13.65 13.70 15.89 15.77 13.40 12.86 12.72 16.58 13.15 14.75 12.82 14.06 14.05 13.87 12.87 12.29 14.44 15.98 11.97 10.09 14.54  TC#2  13.84 13.51 15.40 14.22 13.66 13.85 12.99 14.57 13.54 15.68 14.20 14.79 16.18 16.58 14.26 13.26 14.26 16.89 15.00 14.88 13.16 14.75 14.56 15.23 14.71 14.58 16.40 16.00 12.97 11.55 14.57  TC#3  13.30 13.18 14.96 13.57 12.90 13.09 12.30 14.01 12.75 15.12 13.60 14.24 15.75 16.03 13.91 13.09 13.63 16.27 13.94 14.38 12.86 14.40 14.29 14.50 13.79 13.60 15.73 15.40 12.47 11.19 14.30  TC#4  14.31 13.76 15.11 14.24 13.97 13.70 12.78 13.98 13.56 15.29 14.56 14.90 15.69 16.49 14.71 13.88 13.50 16.21 14.44 14.79 13.59 14.65 14.91 14.88 14.43 14.13 16.33 15.88 13.74 12.50 14.50  TC#5  14.21 13.54 15.02 14.05 13.70 13.37 12.55 13.63 13.20 15.12 14.44 14.75 15.57 16.34 14.61 13.83 13.24 16.03 14.05 14.68 13.47 14.55 14.81 14.73 14.09 13.80 16.09 15.76 13.59 12.40 14.43  TC#6  -  14.95 14.05 15.72 14.22 13.95 14.12 13.13 14.80 13.95 15.54 14.48 15.00 16.18 16.61 14.76 13.68 14.01 16.98 15.28 15.38 13.76 14.88 14.68 15.23 14.91 14.68 16.45 16.53 13.54 12.16 14.87  TC#7  14.35 13.68 15.25 13.72 13.26 13.45 12.57 14.28 13.26 14.95 13.90 14.56 15.79 16.05 14.36 13.44 13.43 16.52 14.52 14.93 13.44 14.53 14.44 14.74 14.24 13.93 15.91 16.13 13.14 11.78 14.65  TC#8  12.70 12.71 15.19 12.85 11.55 12.13 11.05 13.09 11.37 13.91 13.65 13.70 15.89 15.77 13.40 12.86 12.72 16.58 13.15 14.75 12.82 14.06 14.05 13.87 12.87 12.29 14.44 15.98 11.97 10.09 14.54  BARK ORIG  South Campus Log Total Summary Data 1993. Daily MINIMUM  13.67 13.15 15.73 13.37 12.35 12.71 11.61 13.52 12.09 14.35 13.74 14.19 16.04 16.32 13.88 13.06 13.13 16.85 13.72 14.88 13.03 14.24 14.17 14.38 13.41 12.80 14.95 15.83 12.43 10.44 14.57  BARK NEW  August  213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239  J.D.  17.98 19.82 20.51 22.12 22.96 22.09 20.55 20.77 18.88 17.69 17.61 18.33 18.11 17.36 17.14 17.69 17.74 17.63 18.93 19.60 18.43 17.56 17.28 15.54 14.78 15.57 16.50  CR10 TEMP 13.01 15.84 16.38 17.30 17.14 14.48 13.76 16.15 14.87 14.22 12.77 12.61 11.98 13.30 14.20 13.46 13.93 12.45 15.22 14.44 13.46 14.30 13.14 12.85 8.85 9.91 11.91  AIR TEMP 69.19 69.15 43.99 31.46 49.47 73.40 74.20 65.19 86.80 81.40 69.32 77.50 76.30 81.70 77.40 91.80 65.56 72.30 73.00 63.10 82.30 71.10 65.73 63.87 67.95 76.30 76.30  RH%  13.24 15.33 16.40 17.19 17.80 16.36 14.36 17.53 15.39 13.48 11.75 12.35 12.70 13.80 14.98 14.20 16.35 12.25 13.69 13.90 14.54 14.77 12.86 12.11 8.44 9.37 12.50  BARK TEST 13.80 15.83 16.79 17.88 18.60 17.18 15.13 18.14 15.77 13.99 12.40 12.98 13.21 14.47 15.16 14.97 17.00 12.80 13.99 14.36 15.02 14.88 13.46 12.73 8.96 9.80 12.99  TC#1  -  12.73 14.92 15.75 16.74 17.39 15.81 13.74 17.33 15.22 13.17 11.31 11.72 12.01 13.37 14.86 13.57 15.76 11.66 13.07 13.26 14.04 14.57 12.36 12.06 7.81 8.72 11.94  TC#2  14.75 16.90 17.92 18.76 19.32 18.06 16.35 18.21 15.72 14.43 13.43 14.22 14.04 14.24 15.30 15.00 16.73 13.79 15.11 15.43 15.38 14.90 13.97 13.24 10.28 11.10 13.34  TC#3  13.90 16.24 17.29 17.83 18.29 17.07 15.39 17.58 15.37 14.07 12.67 13.29 13.26 13.91 15.10 14.15 16.90 13.03 14.36 14.62 14.70 14.67 13.31 12.83 9.45 10.46 12.74  TC#4  14.28 16.61 17.91 18.18 18.67 18.07 16.76 17.59 16.16 15.16 13.92 14.09 14.43 14.59 15.45 15.19 15.86 13.65 15.13 15.08 15.42 15.22 14.79 13.63 10.77 11.12 13.34  TC#5  14.01 16.30 17.71 17.79 18.25 17.68 16.39 17.39 16.06 15.08 13.64 13.71 14.18 14.44 15.39 14.87 15.48 13.26 14.81 14.77 15.17 15.11 14.59 13.46 10.40 10.77 13.14  TC#6  -  14.85 17.00 17.89 18.88 19.56 18.46 16.94 18.28 16.13 14.78 14.01 14.62 14.85 14.95 15.38 16.05 16.46 14.20 15.65 15.84 15.98 15.37 14.42 13.61 11.09 11.64 13.89  TC#7  14.28 16.53 17.44 18.21 18.78 17.72 16.17 17.85 15.77 14.55 13.44 13.94 14.21 14.59 15.20 15.42 16.38 13.58 15.08 15.25 15.38 15.13 13.99 13.23 10.42 11.10 13.49  TC#8  12.73 14.92 15.75 16.74 17.39 15.81 13.74 17.33 15.22 13.17 11.31 11.72 12.01 13.37 14.86 13.57 15.76 11.66 13.07 13.26 14.04 14.57 12.36 12.06 7.81 8.72 11.94  BARK ORIG  South Campus Log Total Summary Data 1993. Daily MINIMUM  —  13.24 15.33 16.40 17.19 17.80 16.36 14.36 17.53 15.39 13.48 11.75 12.35 12.70 13.80 14.98 14.20 16.35 12.25 13.69 13.90 14.54 14.77 12.86 12.11 8.44 9.37 12.50  BARK NEW  8.84 10.26 9.62 12.01 11.40  14.07 14.87 14.42 13.98 14.23 15.49 15.92 18.90 17.61 15.62 13.36 14.08 14.55 18.07 17.99 17.04 17.43 15.88 16.14 16.17 14.71  12.36 11.58 11.60 11.86 13.02  16.21 15.83 16.89 15.28 15.94 17.34 18.31 19.46 20.02 18.82 16.64 16.14 16.79 18.90 20.22 20.36 20.28 20.06 19.10 18.71 17.79  Mayl2l 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151  AIR TEMP  CR10 TEMP  J.D.  92.90 86.70 89.40 93.50 88.90 82.00 82.70 68.66 83.50 90.10 97.40 87.60 86.20 66.71 72.10 82.40 87.60 92.30 86.10 90.30 100.00  97.40 81.00 90.80 87.30 89.20  RH% BARK TEST  21.79 18.56 17.50 15.71 19.93 21.44 21.19 22.37 22.83 20.04 15.25 20.04 19.14 21.19 23.68 24.83 24.11 22.65 22.17 21.96 16.79  10.37 14.30 10.98 14.51 14.32  TC#1  -  21.95 18.67 17.41 15.70 20.19 21.62 21.19 22.54 22.89 20.11 15.14 20.41 19.08 21.51 23.83 25.00 24.20 22.63 22.28 22.02 16.52  10.08 14.67 10.84 14.84 14.23  TC#2  19.03 17.03 16.92 14.91 17.55 19.09 19.13 19.88 20.41 17.43 14.31 17.57 17.82 19.47 20.35 21.46 21.04 19.57 19.68 19.68 16.26  9.87 11.63 10.20 12.99 12.92  TC#3  18.94 17.11 16.82 14.81 17.57 19.15 19.06 19.89 20.25 17.16 14.12 17.71 17.84 19.59 20.12 21.36 20.81 19.32 19.59 19.44 15.94  9.61 11.71 10.05 13.14 12.70  TC#4  14.25 14.11 14.58 13.65 14.29 15.13 15.87 17.22 17.65 16.20 14.13 13.98 14.40 16.30 17.08 17.27 17.44 17.04 16.13 16.30 15.77  9.75 9.83 9.66 10.94 11.68  TC#5  14.31 14.19 14.56 13.64 14.35 15.18 15.90 17.27 17.65 16.18 14.10 14.05 14.44 16.39 17.12 17.29 17.47 17.02 16.13 16.32 15.71  9.69 9.92 9.65 11.04 11.68  TC#6  -  16.40 15.67 15.90 14.65 16.47 17.79 18.08 19.55 19.77 17.33 14.47 15.96 16.16 18.73 20.07 20.45 20.27 18.93 18.30 18.15 15.98  10.12 11.42 10.26 12.34 12.76  TC#7  16.54 15.80 15.81 14.60 16.57 17.85 18.06 19.63 19.67 17.21 14.29 16.10 16.20 18.89 20.07 20.44 20.24 18.83 18.31 18.13 15.74  9.84 11.61 10.12 12.56 12.62  TC#8  21.95 18.67 17.41 15.70 20.19 21.62 21.19 22.54 22.89 20.11 15.14 20.41 19.08 21.51 23.83 25.00 24.20 22.63 22.28 22.02 16.52  10.08 14.67 10.84 14.84 14.23  BARK ORIG  South Campus Log Total Summary Data 1993. Daily AVERAGE BARK NEW  CR10 TEMP  17.36 17.23 19.54 18.04 18.13 18.90 16.82 16.44 15.87 15.60 15.18 16.68 16.50 16.77 17.38 18.63 19.17 22.69 20.03 19.03 17.78 15.59 16.12 17.70 19.46 20.08 19.01 17.97 18.56 19.21  J.D.  Junel52 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 15.45 14.57 18.58 14.93 16.35 16.74 14.83 14.69 12.66 14.82 13.25 14.72 14.05 14.88 15.62 16.87 16.97 20.05 16.04 15.64 13.52 12.78 14.96 15.84 18.07 17.69 15.50 16.22 16.50 16.52  AIR TEMP 90.30 95.70 77.60 96.20 92.80 91.60 88.50 78.50 94.10 78.40 87.60 81.70 89.50 96.80 93.40 91.40 89.50 78.80 76.80 85.80 89.90 85.00 76.90 75.20 80.50 89.20 78.80 84.30 80.20 82.40  RH%  19.39 17.82 17.95 18.76 16.79 16.28 15.68 18.19 15.41 17.86 16.10 15.78 17.59 20.26 20.17 0.00 24.73 22.35 16.32 18.15 19.94 22.03 26.26 22.06 22.04 24.50 24.70 22.32  BARK TEST 20.23 19.07 29.78 20.46 19.98 19.30 18.54 20.05 15.04 15.43 14.99 16.51 16.33 16.57 17.19 18.45 18.90 0.00 24.82 22.50 16.53 18.27 20.24 22.46 26.58 22.31 22.70 24.99 25.12 22.58  TC#1  -  20.49 19.08 30.46 20.42 20.03 19.25 18.66 20.27 14.83 23.05 17.82 21.60 18.21 16.75 21.18 24.86 24.14 0.00 24.93 22.48 16.25 18.56 20.59 22.75 26.97 22.25 22.96 25.68 25.69 22.65  TC#2  18.66 17.35 24.62 18.05 19.14 18.10 17.06 16.98 14.53 23.86 18.01 21.92 18.23 16.66 21.50 25.20 24.38 0.00 21.44 19.94 16.30 15.28 17.99 19.40 22.61 20.22 20.18 20.98 20.87 19.45  TC#3  18.71 17.11 24.71 17.67 19.21 17.87 17.00 16.84 14.31 16.96 15.23 18.40 16.43 15.80 19.16 20.30 21.06 0.00 21.12 19.61 15.98 15.13 18.10 19.17 22.53 19.90 20.00 20.91 20.80 19.13  TC#4  15.04 15.09 17.73 16.08 16.05 16.61 14.90 14.63 13.38 17.09 15.19 18.44 16.24 15.62 19.21 20.11 21.00 0.00 17.61 16.60 14.67 13.49 14.95 16.03 18.41 17.96 16.73 16.63 17.11 17.12  TC#5  15.08 15.08 17.87 16.06 16.12 16.60 14.89 14.68 13.38 13.96 13.29 14.72 14.26 15.12 15.73 17.01 17.21 0.00 17.61 16.63 14.62 13.55 15.07 16.08 18.51 17.94 16.73 16.78 17.20 17.12  TC#6  -  16.88 16.68 22.19 17.60 17.57 17.81 15.94 16.83 14.11 14.19 13.38 14.83 14.28 15.13 15.81 17.10 17.28 0.00 20.32 18.89 15.50 15.11 16.90 18.52 21.50 19.99 18.56 19.88 20.39 19.76  TC#7  17.02 16.62 22.52 17.45 17.66 17.73 15.96 16.84 13.90 17.77 15.38 17.76 16.18 15.92 17.44 20.14 20.13 0.00 20.19 18.76 15.22 15.17 17.06 18.56 21.63 19.80 18.54 20.13 20.54 19.65  TC#8  20.49 19.08 30.46 20.42 20.03 19.25 18.66 20.27 14.83 23.05 17.82 21.60 18.21 16.75 21.18 24.86 24.14 0.00 24.93 22.48 16.25 18.56 20.59 22.75 26.97 22.25 22.96 25.68 25.69 22.65  BARK ORIG  South Campus Log Total Summary Data 1993. Daily AVERAGE  19.39 17.82 17.95 18.76 16.79 16.28 15.68 18.19 15.41 17.86 16.10 15.78 17.59 20.26 20.17 0.00 24.73 22.35 16.32 18.15 19.94 22.03 26.26 22.06 22.04 24.50 24.70 22.32  BARK NEW  CR10 TEMP  17.99 18.27 18.74 18.77 19.06 18.53 18.76 19.22 19.11 19.47 18.69 18.34 19.16 19.65 18.21 17.91 18.90 20.58 19.74 18.49 17.28 17.38 17.90 18.85 19.65 20.17 20.62 19.77 17.47 16.79 18.59  J.D.  Ju1y182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 14.94 16.44 15.25 16.45 15.39 15.21 15.89 15.87 15.95 16.92 14.84 16.39 16.94 16.35 14.57 15.79 16.87 17.57 16.57 14.82 15.52 15.64 16.04 16.53 16.77 17.24 18.16 16.72 14.09 15.54 17.30  AIR TEMP 89.20 87.40 92.20 86.90 87.30 87.30 88.90 89.20 87.50 82.80 93.20 88.90 87.80 9310 95.30 92.30 88.30 84.30 92.90 96.60 87.70 95.00 91.80 88.10 89.30 87.70 88.90 94.80 96.10 89.40 86.10  RH%  17.56 22.14 18.81 22.50 21.67 19.80 22.38 22.22 21.77 21.93 20.22 21.48 24.33 21.94 16.60 20.61 23.46 26.09 22.32 17.29 18.22 17.14 20.17 23.62 23.17 23.43 20.44 19.24 15.94 18.42 22.33  BARK TEST 17.80 22.59 19.21 23.22 22.38 20.53 22.83 22.95 22.28 22.67 20.80 22.01 24.90 22.48 17.01 21.07 23.91 26.59 22.80 17.47 18.72 17.40 20.57 24.14 23.88 23.88 20.93 19.73 16.29 18.68 22.95  TC#1  -  17.72 23.03 19.06 23.59 22.41 20.41 23.08 22.99 22.38 22.87 20.85 22.27 25.27 22.40 16.79 21.44 24.31 26.82 22.86 17.21 18.99 17.34 20.84 24.50 23.91 23.98 20.76 19.70 16.20 19.14 23.30  TC#2  16.82 20.26 18.60 21.11 20.98 20.15 20.71 21.05 21.00 20.80 18.73 19.98 21.98 21.48 16.29 19.81 21.10 23.41 19.74 16.51 17.50 17.00 19.43 21.67 22.38 22.16 20.90 18.29 14.95 16.27 21.20  TC#3  16.63 20.29 18.36 21.09 20.72 19.89 20.60 20.81 20.74 20.62 18.37 19.84 21.83 21.27 15.95 19.90 20.99 23.13 19.30 16.22 17.55 16.97 19.47 21.48 22.24 21.98 20.74 17.96 14.75 16.38 21.36  TC#4  15.52 16.49 16.22 16.81 16.58 15.99 16.20 16.64 16.42 17.20 16.13 16.49 17.54 17.74 15.57 15.89 16.66 18.32 17.12 15.90 15.22 15.65 16.25 17.05 17.62 17.61 18.15 17.31 14.74 14.76 16.93  TC#5  15.47 16.57 16.17 16.85 16.54 15.94 16.22 16.62 16.38 17.18 16.09 16.50 17.55 17.67 15.49 15.93 16.70 18.30 17.06 15.81 15.23 15.65 16.26 17.06 17.59 17.56 18.07 17.26 14.72 14.80 17.00  TC#6  -  16.79 18.71 17.40 19.01 18.69 17.66 18.83 19.18 18.77 19.62 17.51 18.49 20.31 19.39 16.38 17.49 19.48 21.57 19.83 16.89 16.72 16.48 17.69 19.46 19.92 20.08 19.40 18.30 15.57 16.41 19.24  TC#7  16.62 18.88 17.23 19.18 18.62 17.54 18.91 19.13 18.73 19.66 17.35 18.56 20.40 19.25 16.15 17.66 19.64 21.54 19.72 16.65 16.78 16.43 17.78 19.54 19.90 20.06 19.29 18.18 15.42 16.58 19.44  TC#8  17.72 23.03 19.06 23.59 22.41 20.41 23.08 22.99 22.38 22.87 20.85 22.27 25.27 22.40 16.79 21.44 24.31 26.82 22.86 17.21 18.99 17.34 20.84 24.50 23.91 23.98 20.76 19.70 16.20 19.14 23.30  BARK ORIG  South Campus Log Total Summary Data 1993. Daily AVERAGE  17.56 22.14 18.81 22.50 21.67 19.80 22.38 22.22 21.77 21.93 20.22 21.48 24.33 21.94 16.60 20.61 23.46 26.09 22.32 17.29 18.22 17.14 20.17 23.62 23.17 23.43 20.44 19.24 15.94 18.42 22.33  BARK NEW  CR10 TEMP  20.35 21.87 22.95 24.52 25.18 23.91 22.19 21.61 19.73 19.08 19.74 19.99 19.15 17.93 18.17 18.12 19.83 19.74 20.91 21.42 19.54 18.17 18.30 16.87 16.68 17.12 17.91  J.D.  Aug213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 18.31 19.58 21.46 23.82 22.56 18.73 17.61 18.51 16.20 16.82 17.12 16.76 15.90 15.29 16.44 16.11 18.68 17.38 18.73 18.82 15.49 16.98 16.40 14.84 13.82 14.51 15.63  AIR TEMP 87.90 88.60 79.00 63.92 73.70 88.30 90.60 8140 96.70 94.40 91.30 92.90 89.90 92.30 94.30 96.50 82.50 91.60 91.30 88.70 89.20 93.80 82.30 79.70 87.70 91.30 91.40  RH%  22.49 23.67 25.14 27.57 27.89 24.92 24.53 23.15 18.04 20.71 21.45 22.46 19.65 17.64 20.84 17.53 26.08 20.94 21.95 23.01 17.84 17.85 18.92 18.39 17.82 17.76 20.27  BARK TEST 23.15 23.92 25.59 28.22 28.68 25.94 25.20 23.93 18.40 21.10 21.86 22.88 20.24 18.29 21.15 17.71 26.54 21.24 22.08 23.25 18.24 17.89 19.42 18.98 18.03 18.02 20.62  TC#1  -  23.17 23.87 25.68 28.36 28.66 25.78 25.32 23.99 18.08 21.35 21.93 23.02 20.24 18.35 21.55 17.55 27.22 21.18 22.07 23.31 17.96 17.93 19.55 18.99 17.99 18.07 20.77  TC#2  22.60 23.82 25.07 27.08 27.19 24.62 23.64 21.73 17.56 19.94 21.15 20.72 18.33 17.33 18.31 16.95 25.09 21.09 22.04 21.91 17.40 17.20 18.68 18.48 17.90 16.93 19.28  TC#3  22.53 23.72 25.07 27.10 27.02 24.29 23.46 21.35 17.24 20.05 21.17 20.52 18.00 17.22 18.27 16.82 25.40 21.01 21.98 21.75 16.98 17.21 18.72 18.39 17.84 16.77 19.29  TC#4  17.98 19.39 20.71 21.93 21.89 20.26 18.93 18.81 17.12 16.74 16.93 17.14 16.57 15.86 16.87 16.46 18.46 17.43 18.58 18.72 16.34 16.62 16.39 15.22 14.33 14.33 15.88  TC#5  17.99 19.38 20.72 21.91 21.77 20.09 18.84 18.71 17.04 16.76 16.96 17.09 16.48 15.82 16.90 16.41 18.51 17.41 18.57 18.66 16.18 16.62 16.35 15.15 14.29 14.29 15.85  TC#6  -  20.16 21.32 22.85 24.73 24.93 22.92 21.69 21.11 17.74 18.26 19.09 19.79 18.52 16.93 18.74 17.16 20.88 19.10 20.12 20.82 17.52 17.27 17.31 16.53 16.16 16.23 18.17  TC#7  20.21 21.33 22.95 24.87 24.89 22.73 21.67 21.00 17.46 18.37 19.19 19.81 18.40 16.82 18.89 17.00 21.27 19.15 20.21 20.86 17.25 17.28 17.35 16.48 16.21 16.25 18.27  TC#8  23.17 23.87 25.68 28.36 28.66 25.78 25.32 23.99 18.08 21.35 21.93 23.02 20.24 18.35 21.55 17.55 27.22 21.18 22.07 23.31 17.96 17.93 19.55 18.99 17.99 18.07 20.77  BARK ORIG  South Campus Log Total Summary Data 1993. Daily AVERAGE  UI  22.49 23.67 25.14 27.57 27.89 24.92 24.53 23.15 18.04 20.71 21.45 22.46 19.65 17.64 20.84 17.53 26.08 20.94 21.95 23.01 17.84 17.85 18.92 18.39 17.82 17.76 20.27  BARK NEW  

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